107 Prompt Engineering Jobs

Expected Notice Period: 30 Days Shift: (GMT+05:30) Asia/Kolkata (IST) What do you need for this opportunity Must have skills required: Agent Orchestration, AI-powered SaaS, open-source projects, Prompt Engineering, Python, Micro services, Rest APIs, LLM, Ai products, Amazon AWS, Cloud Services Lyzr is Looking for: What Youll Do : Design and develop backend services that power GenAI applications and platforms Build APIs and infrastructure to support LLM-based features, tools, and agent workflows Collaborate with frontend, ML, and product teams to create seamless AI experiences Optimize backend systems for performance, scalability, and reliability Work with vector databases, data pipelines, and AI model endpoints (OpenAI, Anthropic, Hugging Face, etc.) Maintain clean, secure, and production-grade code Contribute to the architecture and roadmap of our GenAI stack What Were Looking For : 13 years of experience in backend development Proficient in Python Strong experience with REST APIs, microservices, and scalable cloud infrastructure Experience building or supporting GenAI applications and/or LLM-powered products Comfortable working with vector databases (e.g., Pinecone, Weaviate, FAISS) and RAG pipelines Exposure to cloud services (AWS, GCP, or Azure) and containerization (Docker, Kubernetes) Excellent problem-solving, communication, and collaboration skills Nice to Have Experience building and scaling AI-powered SaaS products Contributions to open-source GenAI projects Understanding of prompt engineering and agent orchestration frameworks

Working knowledge of Azure AI Working knowledge of LLM , RAG- Data insights , Reasoning Agent , Chain of thought Knowledge of Graph DB , COSMOS DB , Neo4j Prompt engineering API building Domain knowledge in Finance , data management Should have worked on enterprise AI use cases and one go live solution.

Part-time - Personal Injury Paralegal (AI-Generated Settlement Demand Reviewer) Remote - India Employment Type: Part time Part-Time (10-20 hours per week, flexible schedule) Position Overview Were developing an AI-driven agent to draft settlement demand notes, and we need an experienced Personal Injury Paralegal to review, enhance, and validate the AIs outputs. The ideal candidate will have a strong background in personal injury settlement preparation, exceptional attention to detail, and the ability to identify and correct inaccuracies in AI-generated content. Youll work closely with our legal team and AI engineers to ensure every demand package is accurate, persuasive, and fully compliant with jurisdictional standards. Key Responsibilities Review AI-Generated Drafts Examine settlement demand notes produced by the AI agent for accuracy, completeness, and proper organization. Identify errors or omissions in liability narratives, damage calculations, medical summaries, and policy-limit references. Enhance language for clarity, professionalism, and persuasive impact, ensuring tone aligns with firm standards. Content Improvement & Validation Verify that medical records, bills, wage-loss documentation, and expert opinions are correctly interpreted and summarized Cross-check all numerical values (medical expenses, lost wages, future-care estimates) against source documents. Confirm that statutory deadlines, comparative fault percentages, and damage caps are properly applied. Case File Management Organize and maintain case files (electronic and/or hard copy) so supporting documents align with AI-generated narratives. Tag any missing or inconsistent data points and liaise with attorneys or medical providers to procure necessary information. Legal Research & Compliance Research relevant case law, local court rules, and insurance adjuster guidelines to ensure demand letters meet current jurisdictional requirements. Advise on any new legal developments that should be incorporated into automated templates. Collaboration & Feedback Loop Provide structured feedback to AI engineers regarding common errors, formatting improvements, or language enhancements. Assist in refining prompts and templates to improve future AI drafts. Participate in weekly alignment meetings with attorneys, AI developers, and project managers to review quality metrics and set improvement goals. Drafting & Correspondence After AI review, prepare final settlement demand packagescombining improved narrative, medical summaries, and attachmentsfor attorney approval. Draft follow-up correspondence to insurance adjusters, defense counsel, and expert witnesses when supplemental documentation or clarifications are needed. Quality Control & Reporting Maintain a checklist for each demand package to ensure all elements (liability analysis, damages breakdown, supporting exhibits) are present and accurate. Generate weekly reports tracking AI accuracy scores, number of revisions, and turnaround times. Flag any systemic AI issues to the legal and engineering teams for corrective action. Required Qualifications Minimum 5 years of hands-on Personal Injury Paralegal experiencespecifically with settlement demand preparation and review. Certificate or Associates degree in Paralegal Studies (preferred). Proficiency with case management systems (e.g., Clio, Filevine, MyCase) and document-review platforms. Strong command of medical terminology, billing codes, and damage calculations. Proven ability to draft clear, persuasive settlement demand letters. Excellent written and verbal communication skills with meticulous attention to detail. Experience working with or reviewing AI-generated legal documents (preferred but not mandatory). Ability to work independently, manage deadlines, and juggle multiple files in a fast-paced environment. Reliable internet connection and quiet workspace (for remote work). Desired Skills & Attributes Familiarity with insurance adjuster protocols, and jurisdiction-specific settlement practices. Basic understanding of prompt engineering or experience collaborating with AI/ML teams Advanced Excel skills for damage-analysis spreadsheets. Strong critical thinking and problem-solving aptitudeable to spot subtle inaccuracies or inconsistencies in complex data sets. High level of discretion and ability to maintain confidentiality of client information. Collaborative mindsetcomfortable providing structured feedback to both attorneys and software engineers. Work Schedule & Compensation Schedule: 7:30 PM 11:30 PM , approximately 10-20 hours per week. Occasional urgent requests may require same-day review. Compensation: Competitive hourly rate, commensurate with experience. Benefits:N/A (part-time, hourly). Potential to expand hours or take on additional projects based on performance and firm needs. Location- Remote, Delhi NCR, Bangalore, Chennai, Pune, Kolkata, Ahmedabad, Mumbai, Hyderabad

Experience Required We are looking for an experienced AI Engineer to join our team. The ideal candidate will have a strong background in designing, deploying, and maintaining advanced AI/ML models with expertise in Natural Language Processing (NLP), Computer Vision, and architectures like Transformers and Diffusion Models. You will play a key role in developing AI-powered solutions, optimizing performance, and deploying and managing models in production environments. Key Responsibilities 1. AI Model Development and Optimization: Design, train, and fine-tune AI models for NLP, Computer Vision, and other domains using frameworks like TensorFlow and PyTorch. Work on advanced architectures, including Transformer-based models (e.g., BERT, GPT, T5) for NLP tasks and CNN-based models (e.g., YOLO, VGG, ResNet) for Computer Vision applications. Utilize techniques like PEFT (Parameter-Efficient Fine-Tuning) and SFT (Supervised Fine-Tuning) to optimize models for specific tasks. Build and train RLHF (Reinforcement Learning with Human Feedback) and RL-based models to align AI behavior with real-world objectives., Explore multimodal AI solutions combining text, vision, and audio using generative deep learning architectures. 2. Natural Language Processing (NLP): Develop and deploy NLP solutions, including language models, text generation, sentiment analysis, and text-to-speech systems. Leverage advanced Transformer architectures (e.g., BERT, GPT, T5) for NLP tasks. 3. AI Model Deployment and Frameworks: Deploy AI models using frameworks like VLLM, Docker, and MLFlow in production-grade environments. Create robust data pipelines for training, testing, and inference workflows. Implement CI/CD pipelines for seamless integration and deployment of AI solutions. 4. Production Environment Management: Deploy, monitor, and manage AI models in production, ensuring performance, reliability, and scalability. Set up monitoring systems using Prometheus to track metrics like latency, throughput, and model drift. 5. Data Engineering and Pipelines: Design and implement efficient data pipelines for preprocessing, cleaning, and transformation of large datasets. Integrate with cloud-based data storage and retrieval systems for seamless AI workflows. 6. Performance Monitoring and Optimization: Optimize AI model performance through hyperparameter tuning and algorithmic improvements. Monitor performance using tools like Prometheus, tracking key metrics (e.g., latency, accuracy, model drift, error rates etc.) 7. Solution Design and Architecture: Collaborate with cross-functional teams to understand business requirements and translate them into scalable, efficient AI/ML solutions. Design end-to-end AI systems, including data pipelines, model training workflows, and deployment architectures, ensuring alignment with business objectives and technical constraints. Conduct feasibility studies and proof-of-concepts (PoCs) for emerging technologies to evaluate their applicability to specific use cases. 8. Stakeholder Engagement: Act as the technical point of contact for AI/ML projects, managing expectations and aligning deliverables with timelines. Participate in workshops, demos, and client discussions to showcase AI capabilities and align solutions with client needs. Technical Skills Proficient in Python, with strong knowledge of libraries like NumPy, Pandas, SciPy, and Matplotlib for data manipulation and visualization. Expertise in TensorFlow, PyTorch, Scikit-learn, and Keras for building, training, and optimizing machine learning and deep learning models. Hands-on experience with Transformer libraries like Hugging Face Transformers, OpenAI APIs, and LangChain for NLP tasks. Practical knowledge of CNN architectures (e.g., YOLO, ResNet, VGG) and Vision Transformers (ViT) for Computer Vision applications. Proficiency in developing and deploying Diffusion Models like Stable Diffusion, SDX, and other generative AI frameworks. Experience with RLHF (Reinforcement Learning with Human Feedback) and reinforcement learning algorithms for optimizing AI behaviors. Proficiency with Docker and Kubernetes for containerization and orchestration of AI workflows. Hands-on experience with MLOps tools such as MLFlow for model tracking and CI/CD integration in AI pipelines. Expertise in setting up monitoring tools like Prometheus and Grafana to track model performance, latency, throughput, and drift. Knowledge of performance optimization techniques, such as quantization, pruning, and knowledge distillation, to improve model efficiency. Experience in building data pipelines for preprocessing, cleaning, and transforming large datasets using tools like Apache Airflow, Luigi Familiarity with cloud-based storage systems (e.g., AWS S3, Google BigQuery) for efficient data handling in AI workflows. Strong understanding of cloud platforms (AWS, GCP, Azure) for deploying and scaling AI solutions. Knowledge of advanced search technologies such as Elasticsearch for indexing and querying large datasets. Familiarity with edge deployment frameworks and optimization for resource-constrained environments.

BMC is looking for a Java Tech Lead, an innovator at heart, to join a team of highly skilled software developers, responsible for BMCs Helix Capacity Optimization product. Here is how, through this exciting role, YOU will contribute to BMC's and your own success: Play a vital role in project design to ensure scalability, reliability, and performance are met Design and develop new features as well as maintain existing features by adding improvements and fixing defects in complex areas (using Java) Design and maintain robust AI/ML pipelines using Python and industry-standard ML frameworks . Collaborate closely with AI researchers and data scientists to implement, test, and deploy machine learning models in production. Leverage prompt engineering techniques and implement LLM optimization strategies to enhance response quality and performance. Assist in troubleshooting complex technical problems in development and production Implement methodologies, processes & tools Initiate projects and ideas to improve the teams results On-board and mentor new employees To ensure youre set up for success, you will bring the following skillset & experience: Backend Development: FastAPI, RESTful APIs, Python Cloud Infrastructure: AWS, EKS, Docker, Kubernetes AI/ML Frameworks: LangChain, Scikit-learn, Bedrock, Hugging Face (optional to add if applicable) ML Pipelines: Python, Pandas, NumPy, joblib DevOps & CI/CD: Git, Terraform (optional), Helm, GitHub Actions LLM Expertise: Prompt engineering, RAG (Retrieval Augmented Generation), vector databases (e.g., FAISS, Pinecone) You have 12+ years of experience in Java Backend development You have experience as a Backend Tech Lead You have experience in Spring, Swagger, REST API You worked with Spring Boot, Docker, Kubernetes You are a self-learner whos passionate about problem solving and technology You are a team player with good communication skills in English (verbal and written) Whilst these are nice to have, our team can help you develop in the following skills: Public Cloud (AWS, Azure, GCP) Python, Node.js, C/C++ Automation Frameworks such as Robot Framework

Key Responsibilities: As an Infra AI Automation Programmer you will work on design development and deployment of AI systems that generate content or data often using techniques such as deep learning neural networks and generative models using Python backend coding Meet with clients in and remotely to understand their business objectives challenges and identify potential use cases for Generative AI Assess the client s existing technology infrastructure data landscape and AI maturity to determine the feasibility and best approaches for Gen AI adoption Conduct workshops and discovery sessions to brainstorm Gen AI applications across various business functions e g content creation customer service product development marketing Gen AI Strategy and Solution Design Develop tailored Gen AI strategies and roadmaps for clients in outlining specific use cases implementation plans and expected business outcomes Design Gen AI solutions architecture considering factors such as model selection e g large language models LLMs diffusion models data requirements integration with existing systems and scalability Evaluate and recommend appropriate Gen AI platforms tools and APIs e g OpenAI Google AI Azure AI open source libraries relevant to the client s needs and the Indian market Advise on prompt engineering techniques to optimize the output and performance of Gen AI models for specific client applications Technical Requirements: At least 2 years of programming experience in Python Handson experience in working on Gen AI Handson experience in Tensorflow Pytorch Langchain and Prompt Engineering Experience with vector databases and retrieval augmented generation RAG Familiarity with MLOps principles and tools for deploying and managing Gen AI models Understanding of ethical considerations and responsible AI frameworks Understanding of data structures data modelling SQL NOSQL Object oriented and functional programming GIT Knowledge of basic algorithms and object oriented and functional design principles Deep Knowledge of Mathematics Probability Statistics and Algorithms Good Communication skills Good analytical and problem solving skills Additional Responsibilities: Besides the professional qualifications of the candidates we place great importance in addition to various forms personality profile These include High analytical skills A high degree of initiative and flexibility High customer orientation High quality awareness Excellent verbal and written communication skills Preferred Skills: Technology->Machine Learning->Python,Technology->Machine Learning->TensorFlow,Technology->Machine Learning->Generative AI

An Ideal Candidate: 5+ years in software development; 2+ years in AI tools/frameworks. Technical Skills: Python and .NET development. Multi-agent orchestration (e.g., semantic kernel, autogen). RAG techniques (e.g., GraphRAG). Expertise in Model Context Protocol (MCP). Experience around developing autonomous coding agents and research agents. Preferred Qualifications Experience with distributed systems and cloud-based AI architectures. Knowledge in NLP, knowledge graphs, and semantic reasoning. Experience with Azure DevOps and Azure Cloud Key Competencies: 1.Seeking an AI Developer with a software development background, expertise in AI tools, multi-agent orchestration frameworks, RAG techniques, and Model Context Protocol (MCP). Proficiency in Python, .NET, and hands-on experience with coding agents and research agents is preferable. 2. Responsibilities Build and optimize AI systems using semantic kernel, autogen, and multi-agent frameworks. Develop solutions leveraging retrieval-augmented generation (RAG), preferably GraphRAG. Integrate and optimize workflows using Model Context Protocol (MCP). Write scalable and maintainable code in Python and .NET. Design autonomous coding agents and research agents for problem-solving. 3.Research emerging AI tools and methods for practical application. 4.Debug, troubleshoot, and optimize AI systems for performance and reliability. Ref:JN-062025-794725

Seeking a PHP Full Stack Developer with 3-4 years experience in scalable app development. Must be proficient in frontend & backend tech, and passionate about AI tools and prompt engineering to boost productivity and innovation.

Seeking a Full Stack Python Developer with 3+ years experience in scalable app development. Must be proficient in frontend & backend tech, and passionate about AI tools and prompt engineering to boost productivity and innovation.

Role: ML Engineer. Exp : 5 Years to 10 Years Location : Hyderabad. Job Overview: Were seeking a ML Engineer / Data Scientist to architect agentic AI solutions and own the full ML lifecycle—from proof-of-concept to production. You’ll operationalize LLMs, build agentic workflows, implement MLOps best practices, and design multi-agent systems for cybersecurity tasks. Key Responsibilities: Operationalize large language models and agentic workflows (LangChain, LangGraph, LlamaIndex) to automate security decision-making and threat response. Design, deploy, and maintain multi-agent AI systems for log analysis, anomaly detection, and incident response. Build proof-of-concept GenAI solutions and evolve them into production-ready components on AWS (Bedrock, SageMaker, Lambda, EKS/ECS) using reusable best practices. Implement CI/CD pipelines for model training, validation, and deployment with GitHub Actions, Jenkins, and AWS CodePipeline. Manage model versioning with MLflow and DVC, set up automated testing, rollback procedures, and retraining workflows. Automate cloud infrastructure provisioning with Terraform and develop REST APIs and microservices containerized with Docker and Kubernetes. Monitor models and infrastructure through CloudWatch, Prometheus, and Grafana; analyze performance and optimize costs and SLA compliance. Collaborate with data scientists, application developers, and security analysts to integrate agentic AI into existing security workflows. Qualifications: Bachelor’s or master’s in computer science, Data Science, AI or related quantitative discipline. 4+ years of software development experience, including 3+ years building and deploying LLM-based/agentic AI architectures. In-depth knowledge of generative AI fundamentals (LLMs, embeddings, vector databases, prompt engineering, RAG). Hands-on experience with LangChain, LangGraph, LlamaIndex, Crew.AI or equivalent agentic frameworks. Strong proficiency in Python and production-grade coding for data pipelines and AI workflows. Deep MLOps knowledge: CI/CD for ML, model monitoring, automated retraining, and production-quality best practices. Extensive AWS experience with Bedrock, SageMaker, Lambda, EKS/ECS, S3 (Athena, Glue, Snowflake preferred). Infrastructure as Code skills with Terraform. Experience building REST APIs, microservices, and containerization with Docker and Kubernetes. Solid data science fundamentals: feature engineering, model evaluation, data ingestion. Understanding of cybersecurity principles, SIEM data, and incident response. Excellent communication skills for both technical and non-technical audiences. Preferred Qualifications: AWS certifications (Solutions Architect, Developer Associate). Nice to have Experience with Model Context Protocol (MCP) and RAG integrations. Nice to have Experience in Crew.AI Familiarity with workflow orchestration tools (Apache Airflow). Experience with time series analysis, anomaly detection, and machine learning.

Fast track growth & PnL ownership Handling multiple clients Job Description Proficiency in designing and building REST APIs. Strong understanding of any Cloud platforms such as - GCP/AWS Experience with NoSQL DB or Relational DB Experience with unit testing in any testing framework and maintaining 100% code coverage. Profound knowledge in Serverless design pattern Familiarity with Django or Webapp2 or Flask or similar web app frameworks Experience collaborating with product and design teams. Familiarity with integrating third-party solutions. The Successful Applicant Educational background includes a degree (B.E/B.Tech/M.Tech) in Computer Science, Engineering, or a related field. 8+ years experience as a backend developement. Good understanding in Google cloud platform Knowledge of AI and how to leverage it for day-to-day tasks in backend development. Familiarity with prompt engineering to enhance productivity. Prior experience working with global or regional teams. Experience with agile methodologies and working within cross-functional teams. What's on Offer We've come to realize that we're not merely in the B2B Food service industry we're in the business of Capturing Hearts. We find ourselves in a unique position to turn ordinary, mundane corporate cafeterias into places of pure delight, where individuals can freely express themselves, find inspiration, and share happiness. Such a profound transformation opportunity is a rare gift, where the purpose of our enterprise transcends the ordinary. If this vision resonates with you, we invite you to join us in our mission to spread joy and happiness in a world weighed down by stress and pressure. Together, let's play our part in making this world a more beautiful place.

Genpact (NYSE: G) is a global professional services and solutions firm delivering outcomes that shape the future. Our 125,000+ people across 30+ countries are driven by our innate curiosity, entrepreneurial agility, and desire to create lasting value for clients. Powered by our purpose - the relentless pursuit of a world that works better for people - we serve and transform leading enterprises, including the Fortune Global 500, with our deep business and industry knowledge, digital operations services, and expertise in data, technology, and AI. Inviting applications for the role of Principal Consultant - Generative AI In this role, you will be responsible for creating cutting-edge artificial intelligence solutions that possess a broad understanding of diverse tasks and domains. You will contribute to the development of intelligent systems capable of adapting and learning across a wide range of applications. Responsibilities . experience in Cloud & Generative AI . Hands-on knowledge in Large Language Models from OpenAI, Meta, Google, Hugging Face etc. - demonstrate ability to implement solutions leveraging LLMs . Working knowledge of generative models, prompt engineering, fine-tuning - to implement innovative AI use cases . Collaborate with the architect to develop prototypes, conduct PoCs . Collaborate with service line teams to design, implement and manage Gen-AI solutions . Define and document best practices and strategies regarding deployment and infrastructure maintenance . Good understanding of AWS/Azure primarily focus on AI ecosystems such as Elasticsearch, Azure OpenAI/Cognitive services . Ability to write robust code in Python Java, React, RDBMS (Postgres) - Transactional and Analytical databases . (More than 1 language including Python is preferred) . Experience with Docker and Kubernetes . Experience with Agile Development. Qualifications we seek in you! Minimum Qualifications / Skills . BE/B.TECH . Strong understanding of generative AI models and algorithms. . Proficiency in at least one Generative AI Model (OpenAI ChatGPT, llama, Claude 2, etc.). Preferred Qualifications/ Skills . Self-starter . Highly motivated/passionate for new technologies, engineering mindset . Strong teamwork, problem-solving, and analytical skills . Good communication Genpact is an Equal Opportunity Employer and considers applicants for all positions without regard to race, color, religion or belief, sex, age, national origin, citizenship status, marital status, military/veteran status, genetic information, sexual orientation, gender identity, physical or mental disability or any other characteristic protected by applicable laws. Genpact is committed to creating a dynamic work environment that values respect and integrity, customer focus, and innovation. Get to know us at www.genpact.com and on X, Facebook, LinkedIn, and YouTube. Furthermore, please do note that Genpact does not charge fees to process job applications and applicants are not required to pay to participate in our hiring process in any other way. Examples of such scams include purchasing a %27starter kit,%27 paying to apply, or purchasing equipment or training.

About the Role We are seeking a talented AI Engineer with 2-3 years of professional experience to join our growing team. As a AI Engineer, you will collaborate with data scientists, software engineers, and product teams to design, build, and deploy ML models that drive value across our organisation. This is an excellent opportunity for someone early in their ML career who wants to gain hands-on experience with real-world applications while working alongside experienced professionals. Responsibilities Implement and optimize ML algorithms and models based on requirements from data scientists and product teams Work with Large Language Models (LLMs) to develop AI-powered applications and features Design prompts, fine-tune, and evaluate LLM performance for specific use cases Build systems to integrate LLMs with existing products and services Design and develop ML/DL pipelines for data preprocessing, model training, evaluation, and deployment Experience in using RAG Collaborate with software engineers to integrate ML/DL models into production systems Monitor and maintain deployed ML/DL models, ensuring reliability and performance Participate in code reviews and contribute to engineering best practices Stay current with the latest ML/DL research and technologies, evaluating their potential application to business problems Assist in collecting and preparing datasets for model training and validation Document model architecture, data flows, and deployment procedures Strong in Machine Learning and Deep learning Basics Requirements Bachelor's degree in Computer Science, Statistics, Applied Mathematics, or a related field (Master's preferred but not required) 1-2 years of professional experience building and deploying machine learning models Strong programming skills in Python and familiarity with ML frameworks such as TensorFlow, PyTorch, or scikit-learn Experience with Large Language Models (LLMs), including understanding of transformer architectures, fine-tuning approaches, and prompt engineering Knowledge of NLP concepts and techniques applicable to LLMs (embeddings, tokens, context windows, etc.) Experience with data processing libraries like Pandas, NumPy, and visualization tools like Matplotlib or Seaborn Understanding of ML fundamentals, including supervised/unsupervised learning, feature engineering, and model evaluation Knowledge of software engineering best practices (version control, testing, CI/CD) Basic understanding of cloud platforms (AWS, GCP, or Azure) and containerization (Docker)

As Lead ML Engineer , you'll lead the development of predictive models for demand forecasting, customer segmentation, and retail optimization, from feature engineering through deployment. As Lead ML Engineer, you'll lead the development of predictive models for demand forecasting, customer segmentation, and retail optimization, from feature engineering through deployment. Responsibilities: Build and deploy models for forecasting and optimization Perform time-series analysis, classification, and regression Monitor model performance and integrate feedback loops Use AWS SageMaker, MLflow, and explainability tools (e.g., SHAP or LIME)

We are seeking a passionate and driven Generative AI Engineer to design, develop, and deploy innovative AI applications using Large Language Models (LLMs). The ideal candidate will have hands-on experience with prompt engineering, Python programming, and foundational knowledge of AI orchestration frameworks like LangChain and LangGraph. Experience with the Model Context Protocol (MCP) is a significant advantage. You will work closely with senior AI engineers and cross-functional teams to bring cutting-edge generative AI solutions to life Role & responsibilities Generative AI Application Development: Design, build, and deploy AI applications leveraging LLMs for various use cases such as RAG (Retrieval-Augmented Generation) based chatbots, intelligent agents, content generation, and more. Prompt Engineering: Develop, test, and optimize advanced prompt engineering techniques (e.g., few-shot, Chain-of-Thought, ReAct) to enhance LLM performance, accuracy, and user experience. LLM Orchestration with LangChain & LangGraph: Utilize LangChain and LangGraph to build robust, stateful, and multi-agent AI systems, managing complex conversational flows and integrating external tools and data sources. Python Development: Write clean, efficient, and well-documented Python code for AI model integration, data preprocessing, API development, and general application logic. Model Context Protocol (MCP): Implement and leverage MCP for seamless interaction between LLMs and external systems, ensuring efficient context management and secure communication (if applicable to project needs). Model Evaluation & Testing: Assist in evaluating the performance of generative AI models, defining relevant metrics, and conducting rigorous testing to ensure reliability and effectiveness. Collaboration: Work collaboratively with data scientists, machine learning engineers, product managers, and other stakeholders to translate business requirements into technical solutions. Research & Innovation: Stay updated with the latest advancements in generative AI, LLMs, and related frameworks, and actively experiment with new approaches to improve existing solutions. Deployment & MLOps (Basic): Contribute to the deployment of AI models and understand basic MLOps practices for model versioning, monitoring, and continuous improvement. . Required Qualifications: Bachelor's or Master's degree in Computer Science, Engineering, Data Science, Artificial Intelligence, or a related quantitative field. 1-3 years of hands-on experience in machine learning, software development, or data science, with exposure to AI/ML projects. Strong proficiency in Python programming and familiarity with relevant libraries (e.g., NumPy, Pandas). Proven experience with LangChain for building LLM-powered applications and chaining together various components. Familiarity with LangGraph for orchestrating complex, stateful multi-agent workflows. Hands-on experience with prompt engineering and optimizing prompts for LLMs. Understanding of Large Language Models (LLMs) and their underlying concepts. Experience or strong understanding of Model Context Protocol (MCP) for connecting LLMs with external tools and data sources. Excellent problem-solving skills and a proactive approach to challenges. Strong communication and interpersonal skills, with the ability to articulate technical concepts clearly.) Preferred Skills : Experience with cloud platforms (Azure, AWS, GCP) for deploying AI/ML solutions. Microsoft Certified: Azure AI Engineer Associate (AI-102) or similar AI/ML certification. Familiarity with vector databases (e.g., Pinecone, Chroma, FAISS). Experience with deep learning frameworks such as TensorFlow or PyTorch. Knowledge of Natural Language Processing (NLP) techniques beyond LLMs. Experience in building conversational AI systems or chatbots

Role & responsibilities We are looking for Senior Gen AI Engineer permanent position with MNC company for Remote. Preferred candidate profile Senior Gen AI Engineer GenAI / ML (Python, Langchain) Full Time Focus: Hands-on engineering role focused on designing, building, and deploying Generative AI and LLM-based solutions. The role requires deep technical proficiency in Python and modern LLM frameworks with the ability to contribute to roadmap development and cross-functional collaboration. Key Responsibilities: Design and develop GenAI/LLM-based systems using tools such as Langchain and Retrieval-Augmented Generation (RAG) pipelines. Implement prompt engineering techniques and agent-based frameworks to deliver intelligent, context-aware solutions. Collaborate with the engineering team to shape and drive the technical roadmap for LLM initiatives. Translate business needs into scalable, production-ready AI solutions. Work closely with business SMEs and data teams to ensure alignment of AI models with real-world use cases. Contribute to architecture discussions, code reviews, and performance optimization. Skills Required: Proficient in Python, Langchain, and SQL. Understanding of LLM internals, including prompt tuning, embeddings, vector databases, and agent workflows. Background in machine learning or software engineering with a focus on system-level thinking. Experience working with cloud platforms like AWS, Azure, or GCP. Ability to work independently while collaborating effectively across teams. Excellent communication and stakeholder management skills. Preferred Qualifications: Hands-on experience in LLMs and Generative AI techniques. Experience contributing to ML/AI product pipelines or end-to-end deployments. Familiarity with MLOps and scalable deployment patterns for AI models. Prior exposure to client-facing projects or cross-functional AI teams.

Role & responsibilities Strong understanding of machine learning principles Familiarity with deep learning concepts and frameworks Development, training, deployment and fine tuning of large language models Azure Open AI, Prompt Engineering, LangGraph Agentic Interested share your details to uthirakumar.k@tekskills.in Full Name as Per Pan Card : Email id - Contact number: Alternative Number and Mail ID : Total Exp in IT industry: Relevant experience (Particular skill as per JD): Current CTC ( fixed and variable) : Expected CTC (in INR): Official Notice Period: If Serving Notice Period When is your LWD: Any offers in hand?: (Y/N): Do you have any career Gap?: Current Location: Preferred Location: Reason for job change:

Hi all, We are hiring for the role Generative AI Engineer Experience: 3 - 6 Years Location: Bangalore Notice Period: Immediate - 15 Days Skills: Generative AI Engineer Position Overview: We are looking for a Generative AI Engineer with expertise in Azure OpenAI and hands-on experience with models such as GPT-4o, GPT-o1, and open source LLMs like Llama, mistral. You will work on GenAI solutions development, RAG, fine-tuning, and deploying resources in Azure environment. Proficiency in prompt engineering, Python, PostgreSQL, FastAPI, Streamlit, Django and Angular is essential. This role also requires strong skills in AI models orchestration using intent mapping, Semantic Kernel or function calling, along with proficiency in presentation and public speaking. Key Responsibilities: • RAG, fine-tune, and deploy Azure OpenAI models (e.g., GPT-4o, GPT-o1) and other open-source large language models (LLMs). • Build AI-powered applications using frameworks such as FastAPI, Streamlit, Django, and Angular. • Design and execute AI workflows using tools like prompt flow, Semantic Kernel and implement function calling for complex use cases. • Conduct prompt engineering to improve model performance for specific business cases. • Visualize data and create user interaction insights using Power BI. • Ensure smooth deployment and maintenance of models on Azure cloud infrastructure, including scalability and optimization. • Prepare and deliver presentations, demos, and technical documentation to internal and external stakeholders. • Stay updated with advancements in generative AI, NLP, and machine learning to continuously improve models and methodologies. Required Skills & Qualifications: • Bachelors degree in Computer science, Artificial intelligence, Machine learning, or related field. • At least 2+ year of hands-on experience working on generative AI projects. • Strong expertise in Azure OpenAI models (GPT-4o, GPT-3.5, GPT-o1 etc.). • Proficient in Prompt Engineering, Python, Streamlit, Django, FastAPI, and Angular. • Basics of html, css, javascript, typescript and angular. • Basic understanding of neural networks, machine and transformer architectures. • Experience in retrieval-augmented generation (RAG) and fine-tuning Large language models. • Familiarity with AI model orchestration tools such as Semantic Kernel, intent mapping and function calling techniques. • Excellent public speaking and presentation skills to convey technical concepts to business stakeholders. • Azure Certified AZ900 or AI900 Preferred Qualifications: • Masters degree in Artificial Intelligence, Machine Learning, or related field. • At least 3+ years of experience working on generative AI, NLP, and machine learning projects. • Strong understanding of neural networks, machine learning and transformer architectures. • Implemented GenAI solutions in production. • Familiarity with Automotive Industry • Hands on experience in RAG, RAFT and optimized fine-tuning. • Azure Certified AI-102, DP-100, AZ-204 or DP-203 If you are interested drop your resume at mojesh.p@acesoftlabs.com Call: 9701971793

Wexa AI is looking for Implementation Engineer Interns to help onboard clients and deploy AI co worker tools. A great opportunity to work in real client environments and gain product knowledge. RESPONSIBILITIES AND DUTIES Assist in AI coworker setup and configuration for new clients Work closely with Sales & Product teams to understand client needs Provide technical support during onboarding Document and optimize implementation workflows QUALIFICATIONS REQUIREMENTS Final-year student or recent graduate in Engineering/Tech Basic understanding of APIs, SaaS platforms, or automation tools Strong problem-solving and documentation skills Interest in AI/ML and SaaS product environments

About the job: Key responsibilities: 1. AI Model Development & Integration: Design, implement, and optimize generative AI solutions using various LLMs and foundation models, making strategic decisions on model selection based on use case requirements 2. Advanced Prompt Engineering: Craft sophisticated system prompts and implement complex prompting techniques for optimal model performance across different domains and applications 3. Production AI Applications: Build scalable, production-ready AI applications using LangChain, LangGraph, and Mem0 frameworks with proper error handling and performance optimization 4. Complex Context Management: Develop and maintain advanced conversation flows with persistent context across multi-turn interactions, implementing memory systems and session management 5. Infrastructure & Orchestration: Deploy AI applications using Docker containerization and orchestration platforms, ensuring scalability and reliability in production environments 6. AI Safety & Guardrails: Implement comprehensive guardrails including content filtering, bias detection, response validation, and safety measures for responsible AI deployment 7. System Architecture: Design and implement robust AI system architectures, including API development, database integration, and microservices patterns 8. Performance Optimization: Monitor, debug, and optimize AI system performance, latency, cost efficiency, and resource utilization 9. Model Fine-tuning & Customization: Work on model adaptation, fine-tuning, and customization techniques to meet specific business requirements Who can apply: Only those candidates can apply who: have minimum 1 years of experience Salary: ₹ 2,50,000 - 3,00,000 /year Experience: 1 year(s) Deadline: 2025-07-16 23:59:59 Skills required: Python, Docker, Database Management System (DBMS), APIs, Generative AI Development, LangChain, Prompt Engineering and Memcached Other Requirements: Technical Skills: 1. Advanced Python: Solid foundation in Python. 2. Multi-Model Expertise: Deep hands-on experience with various LLMs (GPT-4, Claude, Llama, Gemini, Mistral) and comprehensive understanding of their capabilities, limitations, and optimal use cases 3. Framework Mastery: Proven experience building production applications with LangChain, LangGraph, and Mem0 frameworks 4. Advanced Prompt Engineering: Expert-level ability to write, optimize, and debug complex system prompts and conversation flows 5. Docker & Orchestration: Strong containerization skills with experience in Docker, or similar orchestration platforms. 6. Production AI Systems: Experience deploying and maintaining AI applications in production environments Professional Experience: 1. GenAI Development: Hands-on experience in generative AI application development 2. Context Management: Proven track record of implementing complex conversation flows and memory systems 3. Guardrails Implementation: Experience implementing AI safety measures, content filtering, and bias detection systems 4. System Architecture: Experience designing scalable AI system architectures and microservices Project Portfolio: 1. Demonstrable GenAI projects with real-world applications 2. Experience with model fine-tuning, RAG systems, or AI agent development 3. Open source contributions or published work in AI/ML domain 4. Production deployments of AI applications with measurable impact About Company: At HD, we're a diverse team of passionate experts offering comprehensive digital solutions. Our commitment to authenticity, innovation, and user-friendliness ensures success in web development, AI/ML, data analytics, backend, and database management. Through collaboration and transparency, we transform visions into exceptional digital realities, empowering clients to succeed. Explore our talented team, insightful blog, and impressive portfolio, and start your exceptional digital journey with us today.

Were seeking a forward-thinking Gen AI Engineer to design, implement, and optimize cutting-edge agentic AI solutions using frameworks such as Crew.ai , LangChain , and LangGraph . You will work at the intersection of LLMs , Retrieval-Augmented Generation (RAG) systems, and NLP , enabling impactful AI applications across diverse domains. Key Responsibilities Design and deploy autonomous AI agents and multi-agent systems using LLMs such as GPT-4o, Claude, and LLaMA, leveraging Crew.ai, LangChain (and LangGraph). Own the AI solution lifecycle , including data acquisition, model experimentation, fine-tuning, deployment, and production monitoring. Develop scalable AI backends and pipelines using Python with frameworks like PyTorch or TensorFlow, deploying via REST APIs (FastAPI) on cloud platforms like AWS or Azure. Implement RAG-based systems by integrating open-source LLMs (via Hugging Face or Ollama) with vector databases (e.g., Pinecone, ChromaDB) and structured data stores (SQL/NoSQL). Collaborate with cross-functional teams to ensure reliable, maintainable, and impactful AI solutions. Required Skills & Experience 2 to 5 years of experience in AI/ML, NLP, Generative AI, with a focus on agentic AI systems . Strong proficiency in Python and hands-on experience building RAG systems and deploying open-source LLMs. Experience developing AI-driven backends and services with a strong understanding of scalability and performance. Familiarity with vector search technologies, database integration, and cloud-native architectures. Excellent communication and collaboration skills; ability to work effectively in a team environment. Education B.Tech/B.E. or M.Tech/M.E. in Computer Science, AI/ML, or a related field. Role: Gen AI Engineer Designation: AI Developer Experience: 2-5 Years (AI/ML, NLP, Generative AI): Location: Pune

NTT DATA strives to hire exceptional, innovative and passionate individuals who want to grow with us. If you want to be part of an inclusive, adaptable, and forward-thinking organization, apply now. We are currently seeking a GenAI + Full-Stack Engineer to join our team in Bangalore, Karntaka (IN-KA), India (IN). 3-8 years of strong hands-on experience in software development, with a focus on AI/ML and Generative AI Hands-on with Generative AI technologies with at least one of the following experiences: Working with Large Language Models (LLMs) such as GPT, LLaMA, Claude, etc. Building intelligent systems using LangGraph, Agentic AI frameworks, or similar orchestration tools Implementing Retrieval-Augmented Generation (RAG), prompt engineering, and knowledge augmentation techniques Proficiency in Python, including experience with data processing, API integration, and automation scripting Demonstrated experience in end-to-end SDLC (Software Development Life Cycle): requirement gathering, design, development, testing, deployment, and support Proficient in CI/CD pipelines and version control systems like Git Experience with containerization technologies such as Docker, and orchestration using Kubernetes Strong problem-solving and debugging skills, with an ability to write clean, efficient, and maintainable code Excellent verbal and written communication skills, with the ability to collaborate effectively across technical and business teams About NTT DATA NTT DATA is a $30 billion trusted global innovator of business and technology services. We serve 75% of the Fortune Global 100 and are committed to helping clients innovate, optimize and transform for long term success. As a Global Top Employer, we have diverse experts in more than 50 countries and a robust partner ecosystem of established and start-up companies. Our services include business and technology consulting, data and artificial intelligence, industry solutions, as well as the development, implementation and management of applications, infrastructure and connectivity. We are one of the leading providers of digital and AI infrastructure in the world. NTT DATA is a part of NTT Group, which invests over $3.6 billion each year in R&D to help organizations and society move confidently and sustainably into the digital future. Visit us at NTT DATA endeavors to make accessible to any and all users. If you would like to contact us regarding the accessibility of our website or need assistance completing the application process, please contact us at . This contact information is for accommodation requests only and cannot be used to inquire about the status of applications. NTT DATA is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or protected veteran status. For our EEO Policy Statement, please click . If you'd like more information on your EEO rights under the law, please click . For Pay Transparency information, please click.

Key Responsibilities: Work with stakeholders to understand requirements and deliver AI solutions across several domains in Wealth Management. Stay updated with the latest advancements in AI and machine learning technologies. Conduct research and experiments to improve AI capabilities within the division. Required Competencies: Retrieval-Augmented Generation (RAG): Experience in developing and implementing RAG models to enhance information retrieval and generation tasks. Vector Stores: Knowledge of Vector Stores for efficient data storage and retrieval. Prompt Engineering: Skills in designing and optimizing prompts for AI models to improve accuracy and relevance. Large Language Model APIs (LLM APIs): Understanding of different LLMs, both commercial and open source, and their capabilities (e.g., OpenAI, Gemini, Llama, Claude). Programming Languages: Proficiency in Python, Java, or other relevant programming languages. Data Analysis: Strong analytical skills and experience with data analysis tools. Problem-Solving: Excellent problem-solving abilities and attention to detail. Communication: Strong verbal and written communication skills. Preferred Competencies: Graph RAG: Proficiency in using Graph RAG for complex data relationships and insights. Knowledge Graphs: Expertise in building and managing Knowledge Graphs to represent and query complex data structures. Machine Learning Frameworks: Experience with TensorFlow, PyTorch, or similar frameworks. Experience with cloud platforms such as AWS, Google Cloud, or Azure. Familiarity with natural language processing (NLP) and computer vision technologies. Previous experience in a similar role or industry. Master s or Ph.D. in Computer Science, Data Science, or a related field. Years of experience: 3-5

About the job: As a Full Stack GenAI Developer at MeetMinutes, you will be responsible for creating cutting-edge AI solutions using Python, Generative AI Development, LangChain, LLM evaluation, LLMOps, JavaScript, React, Amazon Web Services (AWS), Google Cloud Platforms (GCP), Docker, Machine Learning, Natural Language Processing (NLP), PostgreSQL, REST API, FastAPI, GitHub, System Design, and Prompt Engineering. Key responsibilities: 1. Developing and implementing AI algorithms and models to enhance the functionality of our platform. 2. Integrating AI technologies and features into our existing systems to improve user experience. 3. Collaborating with the engineering team to optimize system performance and scalability. 4. Building and maintaining RESTful APIs for seamless communication between different components. 5. Monitoring and troubleshooting any issues related to AI functionality and recommending solutions. 6. Contributing to the overall architecture and design of our AI-driven products. 7. Staying updated on the latest trends and advancements in AI and actively participating in knowledge sharing within the team. If you are passionate about using AI to revolutionize meeting productivity and collaboration, and have a strong background in full-stack development and AI technologies, we'd love to have you join our team! Who can apply: Only those candidates can apply who: have minimum 1 years of experience are Computer Science Engineering students Salary: ₹ 6,50,000 /year Experience: 1 year(s) Deadline: 2025-07-13 23:59:59 Other perks: 5 days a week Skills required: JavaScript, Python, Machine Learning, PostgreSQL, Docker, GitHub, React, REST API, Amazon Web Services (AWS), Natural Language Processing (NLP), Google Cloud Platforms (GCP), FastAPI, Generative AI Development, LangChain, Prompt Engineering, System Design, LLMOps and LLM evaluation About Company: A platform for the future of AI meeting productivity. It is a tool for professionals having conversations in mixed Indian languages and need workflow automations. It has support for Google Meet, MS Teams, and many more meeting platforms. It is a startup recognized by the Ministry of IT and won several accolades working with businesses, IT firms, agencies, listed companies, and SMBs.

As the Engineering manager, you will be managing the roadmap priorities for AI/MLSolution andwill bepoint of contactfor all technical issues and decisions, while managing stakeholders and partners across the organization. Provide technical leadership manage a high-performing engineering team to build and scale our next generationAI Solutions. Hire and directly lead a diverse team of top-tier ML and software engineers, taking charge of allfacetsof AI Products Design, Build,optimize, fine-tune Generative AI/LLM models/AI Solutions that can be integrated withnumerousapplications, support thousands of tenants, andoperateat scale in production to support variousPaypalAI Personalization initiatives Ensure high code quality, performance, and reliability through rigorous testing, code reviews, and adherence to software development best practices. Drive innovation by researching and incorporatingstate-of-the-artmachine learning techniques, tools, and frameworks into the platform. Effective communication, listening, interpersonal, influencing, and alignment driving skills; able to convey important messages in a clear and compelling manner Collaborate with cross-functional teams including product managers, data scientists, and software engineers and stakeholders to define platform requirements and priorities. Develop and evolve engineering processes and collaboration models tooptimizeteam efficiency and collaboration Mentor team members,providetechnical guidance, and foster a culture of collaboration, innovation, and continuous learning. Stay up to date with the latest advancements in AI/ML technology and industry trends andleveragethis knowledge to enhance the platforms capabilities What Do You NeedtoBring Qualifications Proven experience in leading or managing machine learning/AI teams, witha track recordof building successful AI solutions and productizing ML Models, Features Stores Solidtrack recordof over-achieving engineering and platform delivery and scaling targets in high volume, innovative and fast-paced high-pressure environment; proven results in delivery on platform products. Masters / bachelor s in computer science, Computer engineering, Machine Learning, Data Mining, Information Systems, or related disciplines, with technicalexpertisein one or more of the above-mentioned areas or equivalent practical experience. Experience developing Gen AI applications/services usingPrompt Engineering, LLMs, and fine-tuning methodsfor sophisticated business use caseswithlarge amountsof unstructured data. Strong background in deep learning techniques, particularly in NLP and Vision Proficiencyin multiple Programming/scripting languages,i.e.Python, Java, Scala,SQL, NoSQL (like HBase, Redis, Aerospike) Strongproficiencyin machine learning concepts, algorithms, and techniques, with hands-on experience in developing and deploying machine learning models. Expertisein buildingMLpipelines with Big Data technologies such as Hadoop, Spark, HBase, Kafka. Good understanding of distributed systems, data streaming, complex event Processing, NoSQL solutions for creating and managing data integration pipelines for batch and Real Time data needs. Experience with machine learning libraries/frameworks such as TensorFlow, PyTorch, scikit-learn, etc. Experience with cloud platforms (e.g., AWS, Azure, GCP) and containerization technologies (e.g., Docker, Kubernetes). Experience in Azure is a plus Strong communication, listening, interpersonal, influencing, and alignment driving skills; able to convey important messages in a clear and compelling manner Demonstrated leadership abilities, including the ability to inspire, mentor, and empower team members to achieve their full potential. Preferred Prior experience in Content Understanding, enrichment, entity resolution or knowledge graph Strong background in MLOps and experimentation frameworks Extensive experience with concurrent, parallel, and distributed computing, including performance tuning and optimization for large-scale applications