217 Llms Jobs - Page 6

About Us We are a dynamic software testing company with a cutting-edge AI end-to-end testing platform. As a fast-growing startup, we are driven by innovation and a commitment to building intelligent, scalable solutions. We're expanding our content team and looking for a passionate junior content writer who thrives in a fast-paced, collaborative environment. Role Overview As a Junior Content Writer, you'll play a key role in supporting our content and SEO teams. Youll be responsible for producing high-quality written content that communicates our brand effectively and helps us reach our target audience through insightful, original writing. Key Responsibilities Write and edit blog posts, search-optimized articles, website content, and product-related copy Proofread and ensure grammatical accuracy and consistency across all written materials Conduct thorough research to support content accuracy and credibility Assist the content and SEO teams in producing compelling, keyword-rich content Adapt writing style to suit different platforms and target audiences Meet tight deadlines while maintaining quality and attention to detail Requirements Bachelors or Masters degree in Journalism, Mass Communication, Marketing, or related fields 12 years of professional content writing experience, especially in IT and tech domains Comfortable working with technical subject matter; our content often involves topics like software testing, AI/LLMs, test automation, and so on (You dont need to code, but you must be curious and willing to understand) Excellent command of written English with flawless grammar and style Strong research skills and a genuine ability to produce original content (not AI-generated or stitched) Knowledge of SEO principles and ability to apply them to content writing Responsible, accountable, and committed to producing high-quality work on time Team player with a respectful, collaborative attitude Strong work ethic and a willingness to learn and grow How to Apply: Interested candidates are encouraged to submit their resume and a brief cover letter outlining their interest in the position to [HIDDEN TEXT]

Job Description: Python Gen AI Developer Seeking an experienced Python Developer with expertise in Generative AI to join our AI & ML Engineering team. The ideal candidate will work on building intelligent applications leveraging large language models (LLMs) and deep learning to enhance customer experience and streamline business processes. Key Responsibilities: Design, develop, and deploy GenAI solutions using Python and modern AI frameworks. Work with LLMs (e.g., GPT, LLaMA, Claude) and fine-tune them for enterprise use cases. Develop prompt engineering strategies and support prompt optimization. Integrate AI models with backend services and data pipelines. Implement scalable and secure APIs and services for GenAI use cases. Collaborate with data scientists, ML engineers, and product teams. Ensure compliance with enterprise security, data governance, and regulatory standards. Required Skills: 5+ years of experience with Python in enterprise application development. Strong knowledge of GenAI tools (OpenAI, HuggingFace, LangChain, etc.). Experience with LLMs, prompt tuning, RAG (Retrieval Augmented Generation). Experience with Flask/FastAPI or similar frameworks. Familiarity with vector databases (e.g., FAISS, Pinecone). Understanding of NLP and transformer models. Good knowledge of Git, Docker, CI/CD. Nice to Have: Knowledge of Azure OpenAI or AWS Bedrock. Experience working in the finance or banking domain. Exposure to Kubernetes and model deployment pipelines

Role: Python with Gen AI Developer Exp: 7+yrs Budget: Max 28 LPA Location: Bangalore (Hybrid) Must Have: Python libraries and frameworks,Generative AI, Prompt Engineering. Immediate to 30 Days. Ragul 8428065584

We are seeking a Data Scientist to help drive AI-driven insights and solutions, leveraging both traditional machine learning and Generative AI (GenAI). This role focuses on data exploration, predictive modeling, and extracting actionable insights from structured and unstructured data. You will work closely with business teams to translate challenges into AI-powered solutions, using advanced analytics, machine learning, and large language models (LLMs). Key Responsibilities: Conduct exploratory data analysis (EDA) to uncover patterns, trends, and insights. Develop and implement predictive and prescriptive models to support data-driven decision-making. Work with large datasets and apply techniques in statistics, probability, and optimization. Fine-tune large language models (LLMs) for text analytics, summarization, and conversational AI. Leverage Generative AI for knowledge retrieval, document automation, and personalization. Work on A/B testing, experimentation, and causal inference to evaluate AI model effectiveness. Collaborate with business teams to identify AI opportunities and present insights through visualizations. Use vector databases, retrieval-augmented generation (RAG), and prompt engineering for GenAI applications. Assist AI/ML Engineers in transitioning models from research to production while ensuring interpretability and explainability. Stay updated on the latest ML algorithms, generative AI advancements, and statistical techniques. Required Skills & Qualifications: Bachelor's/Master's/PhD in Data Science, Statistics, Mathematics, or a related field. Strong proficiency in Python, SQL for data analysis and modeling. Hands-on experience with statistical modeling, hypothesis testing, and feature engineering. Experience in ML frameworks (Scikit-learn, TensorFlow, PyTorch) and working with LLMs (e.g., GPT, BERT etc). Knowledge of time-series forecasting, clustering, and anomaly detection techniques. Familiarity with NLP, embeddings, and GenAI-driven analytics. Strong experience with data visualization tools. Ability to translate data insights into business impact and storytelling. Exposure to A/B testing, experiment design, and optimization algorithms. About Avaali Headquartered in Bangalore, started in 2013, Avaali Solutions is a leading provider of digital solutions to help reduce operational costs for upper mid to large enterprises. The company has executed over 120+ engagements for large marquee brands across Asia, MEA, and parts of Europe. The company has its product line under Velocious as well as its services and consulting offerings in partnership with various technology vendors. The company has done some of the largest and most complex shared service automation projects and consolidated, standardized, and automated these processes. As a result of their engagements, they have brought about a 35-50% reduction in process cycle time and a 10-15% reduction in cost. Improved visibility, governance, and transparency are other themes that Avaali focuses on via these initiatives. The company has deep skills in technologies such as ML-based ICR/OCR, enterprise content management, workflow automation solutions, chatbot, RPA, and digital signature. The company has a dominant presence in procure-to-pay automation with over 100+ implementations in this space. Some of the prominent clients of Avaali Solutions are Tata Sky, Titan, Sun TV, Bidco Africa, Nayara Energy, and many more.

Hands-on AI & ML Development: Build, train, and deploy ML models from classical techniques (Classification, Regression, Forecasting) to advanced deep learning, LLMs, and Generative AI. Perform feature engineering, statistical analysis, and model tuning to enhance predictive capabilities. Work with big data tools (Hadoop, PySpark, Hive) to process large datasets efficiently. Develop AI-driven solutions tailored for industries like Retail, CPG, BFSI, Healthcare, and eCommerce. Optimize and automate machine learning pipelines for scalable deployment. End-to-End AI/ML Deployment: Own the full ML lifecycle , from development to deployment and monitoring. Collaborate with Data Engineering teams to build production-ready ML pipelines. Work with cloud platforms such as Azure, AWS, GCP, or Databricks for model deployment and monitoring. Design and implement A/B testing strategies to measure model impact. Project Execution & Delivery: Drive multiple AI/ML initiatives from concept to execution , ensuring quality and timely delivery. Partner with cross-functional teams (Product, Data Engineering, Business) to translate business problems into scalable AI solutions . Own project roadmaps, track milestones, and ensure stakeholder alignment. Communicate AI/ML concepts effectively to both technical and non-technical stakeholders . Leadership & Team Growth: Lead by doing mentor and guide a high-performance team of data scientists. Set technical direction, review code, and establish best practices in AI/ML development. Foster a culture of continuous learning, innovation, and hands-on problem-solving . Provide career development guidance and help team members achieve technical excellence. What You Bring to the Table: 8+ years of hands-on experience in Data Science & AI , with strong expertise in ML, Python, and SQL . Exposure to Generative AI Should have worked on at least a few POCs or pilot projects leveraging Gen AI capabilities Deep understanding of ML algorithms , including NLP, LLMs, forecasting, and optimization techniques. Proven track record of building and deploying machine learning models in production environments. Expertise in at least one cloud platform: AWS, Azure, GCP, or Databricks . Strong grasp of statistics, probability, and causal inference . Ability to break down complex AI concepts for business stakeholders. Experience with big data tools (Hadoop, Hive, PySpark) and ML workflow automation . Bonus: Experience with Google Analytics, Adobe Analytics, or digital marketing analytics .

Responsibilities : Build and deploy GenAI applications using LLMs, prompt engineering, and RAG frameworks. Hands-on with prompt engineering, RAG, LLM fine-tuning, and deployment workflows. Implement AI-driven solutions for analyzing, understanding, and migrating legacy codebases. Utilize AI tools to analyze complex legacy systems, identify business logic, dependencies, and potential risks associated with migration. Integrate APIs like OpenAI, Claude, Azure OpenAI, etc., into products or tools. Develop reusable components for prompt handling, embeddings, vector search, etc. Collaborate with designers, BAs, and QA teams to iterate on MVPs and features. Optimize performance, prompt quality, and latency in GenAI pipelines. Requirements : Proficiency in Python, LangChain, LangGraph and GenAI APIs. Hands-on experience with vector databases (Pinecone, FAISS, ChromaDB). Understanding of Agentic AI, LLMs, transformers, and orchestration frameworks. Exposure to cloud services (AWS/GCP/Azure) and CI/CD practices. Stay current with AI trends and tools. Role & responsibilities

About Position: We are conducting an in-person hiring drive for the position of GenAI Developer / Sr. GenAI Developer in Hyderabad. We are looking for an experienced and talented GenAI Developer/Sr. Gen AI Developer to join our growing data competency team. The ideal candidate will have a strong background in working with GEN AI , ML ,LangChain, LangGraph, Agentic AI Microservices (Fast API), Prompt engineering. You will work closely with our data analysts, engineers, and business teams to ensure optimal performance, scalability, and availability of our data pipelines and analytics. Role: GenAI /Sr.GenAI/ RAG / LLM Engineer Interview Location: Gate 11, Argus Block-Sattva Knowledge City, 6th Floor Beside T-hub, Silpa Gram Craft Village, Madhapur Rai Durg, Hyderabad, 500081 Experience: 4 Years-8 Years Job Type: Full Time Employment Note: After joining candidate can work from AII PSL Locations What You'll Do: Develop and fine-tune LLMs for real-world use cases Build and optimize RAG pipelines using Langchain or similar tools Integrate GenAI capabilities into enterprise applications Hands on Python coding exp Work with vector databases and embedding techniques Collaborate with cross-functional teams on AI-driven features Expertise You'll Bring: 4+ years of experience working with data science. Strong proficiency in prompt Engineering and Lang chain and Fast API Experience in Microservices (Fast API), RAG and OpenAI Experience with ML/Ops technologies Understanding of machine learning fundamentals, optimization techniques, generative AI, NLP, LLMs, and Retrieval-Augmented Generation (RAG). Strong analytical, problem-solving, and troubleshooting skills. Ability to work independently and in a collaborative team environment. Python, PyTorch/TensorFlow LLMs (OpenAI, LLaMA, HuggingFace) RAGframeworks (Langchain, LlamaIndex) FAISS, Weaviate, Pinecone Cloud (AWS/GCP/Azure Databricks) Benefits: Competitive salary and benefits package Culture focused on talent development with quarterly promotion cycles and company-sponsored higher education and certifications Opportunity to work with cutting-edge technologies Employee engagement initiatives such as project parties, flexible work hours, and Long Service awards Annual health check-ups Insurance coverage: group term life, personal accident, and Mediclaim hospitalization for self, spouse, two children, and parents Inclusive Environment: Persistent Ltd. is dedicated to fostering diversity and inclusion in the workplace. We invite applications from all qualified individuals, including those with disabilities, and regardless of gender or gender preference. We welcome diverse candidates from all backgrounds. We offer hybrid work options and flexible working hours to accommodate various needs and preferences. Our office is equipped with accessible facilities, including adjustable workstations, ergonomic chairs, and assistive technologies to support employees with physical disabilities. If you are a person with disabilities and have specific requirements, please inform us during the application process or at any time during your employment. We are committed to creating an inclusive environment where all employees can thrive. Our company fosters a values-driven and people-centric work environment that enables our employees to: Accelerate growth, both professionally and personally Impact the world in powerful, positive ways, using the latest technologies Enjoy collaborative innovation, with diversity and work-life wellbeing at the core Unlock global opportunities to work and learn with the industry's best Let's unleash your full potential at Persistent "Persistent is an Equal Opportunity Employer and prohibits discrimination and harassment of any kind."

Experience: 2 + years Expected Notice Period: 30 Days Shift: (GMT+05:30) Asia/Kolkata (IST) Opportunity Type: Office (Pune) Placement Type: Full Time Permanent position Must have skills required: Airflow, LLMs, NLP, Statistical Modeling, Predictive Analysis, Forecasting, Python, SQL, MLFlow, pandas, Scikit-learn, XgBoost As an ML / Data Science Engineer at Anervea, youll work on designing, training, deploying, and maintaining machine learning models across multiple products. Youll build models that predict clinical trial outcomes, extract insights from structured and unstructured healthcare data, and support real-time scoring for sales or market access use cases. Youll collaborate closely with AI engineers, backend developers, and product owners to translate data into product features that are explainable, reliable, and impactful. Key Responsibilities Develop and optimize predictive models using algorithms such as XGBoost, Random Forest, Logistic Regression, and ensemble methods Engineer features from real-world healthcare data (clinical trials, treatment adoption, medical events, digital behavior) Analyze datasets from sources like ClinicalTrials.gov, PubMed, Komodo, Apollo.io, and internal survey pipelines Build end-to-end ML pipelines for inference and batch scoring Collaborate with AI engineers to integrate LLM-generated features with traditional models Ensure explainability and robustness of models using SHAP, LIME, or custom logic Validate models against real-world outcomes and client feedback Prepare clean, structured datasets using SQL and Pandas Communicate insights clearly to product, business, and domain teams Document all processes, assumptions, and model outputs thoroughly Technical Skills Required : Strong programming skills in Python (NumPy, Pandas, scikit-learn, XGBoost, LightGBM) Experience with statistical modeling and classification algorithms Solid understanding of feature engineering, model evaluation, and validation techniques Exposure to real-world healthcare, trial, or patient data (strong bonus) Comfortable working with unstructured data and data cleaning techniques Knowledge of SQL and NoSQL databases Familiarity with ML lifecycle tools (MLflow, Airflow, or similar) Bonus: experience working alongside LLMs or incorporating generative features into ML Bonus: knowledge of NLP preprocessing, embeddings, or vector similarity methods Personal Attributes : Strong analytical and problem-solving mindset Ability to convert abstract questions into measurable models Attention to detail and high standards for model quality Willingness to learn life sciences concepts relevant to each use case Clear communicator who can simplify complexity for product and business teams Independent learner who actively follows new trends in ML and data science Reliable, accountable, and driven by outcomesnot just code Bonus Qualities : Experience building models for healthcare, pharma, or biotech Published work or open-source contributions in data science Strong business intuition on how to turn models into product decisions

We seek a hands-on Delivery Lead with 1012 years of experience to own end-to-end execution of AI/ML projects, mentor technical teams, and collaborate with sales to scale our consulting solutions. Key Responsibilities 1. Project Delivery Own client-facing AI/ML projects from scoping to deployment, ensuring quality, timelines, and business impact. Guide teams on architecture, model design, and deployment (cloud/on-prem). 2. Team Leadership Lead and mentor data scientists/engineers, fostering skill growth and collaboration. Drive best practices in AI/ML (LLMs, MLOps, Agile). 3. Sales Collaboration Partner with sales to scope proposals, estimate efforts, and present technical solutions to clients. Must-Have Skills 10-12 years in AI/ML, with 5+ years leading teams in consulting/client delivery. Expertise in: o AI/ML frameworks (TensorFlow, PyTorch, LLMs). o Cloud platforms (AWS/Azure/GCP) and CI/CD pipelines. o Python/R, data engineering (Spark, Kafka). Strong communication and client/stakeholder management. Good to Have Familiarity with MLOps (Docker, Kubernetes). Agile/Scrum certification. Qualifications Bachelors/Masters in CS, Data Science, or related field. Certifications (e.g., AWS ML, Azure AI Engineer) are a plus.

Job Description: Data Science Trainer We're seeking a committed Technical Data Science Trainer to join us in delivering the next generation of AI technical training. This is not just a job - it's an opportunity to play a key role in empowering the next generation of AI/ML professionals, influencing their careers and contributing to the growing AI ecosystem. The role also helps get recognized as a leader in the AI training space while expanding your personal and professional brand This role is ideal for someone passionate about both teaching and technology, capable of helping learners become skilled professionals in AI and related fields. Skills: AI, Machine Learning, Python, Numpy, Pandas, R Programming, Statistics, Computer Vision, Natural Language Processing, LLMs, Tableau, Power BI Essential Qualifications: B.Tech., M.Tech., MCA or equivalent experience 2 - 6 years' of experience Expertise Required: Technical Expertise: Proficient in AI, ML, Deep Learning, LLMs, Computer Vision, and Python. Tools and Frameworks: Hands-on experience with TensorFlow, PyTorch, Scikit-learn, OpenCV, Hugging Face, NumPy, Pandas, Matplotlib, Seaborn, and R Programming. Communication: Strong ability to explain technical concepts in simple terms and provide clear instructions. Problem-Solving: Ability to debug code, identify errors, and explain solutions effectively. Key Responsibilities: Training Delivery: Design and deliver training programs and workshops for individuals and teams on AI, ML, Deep Learning, LLMs, Computer Vision, and Python programming. Adapt training methods to suit varying levels of expertise, from beginner to advanced learners. Curriculum Development: Develop structured, up-to-date course materials, including slide decks, coding exercises, case studies, and hands-on projects. Incorporate real-world applications and industry best practices into the curriculum for a practical learning experience. Regularly update course content to align with advancements in technology and industry trends. Hands-On Learning: Guide learners through practical exercises, coding labs, and project-based learning to ensure hands-on experience with tools, frameworks, and algorithms. Provide training on key frameworks and tools such as TensorFlow, PyTorch, OpenCV, Hugging Face, Scikit-learn, and Pandas. Mentorship and Support: Offer one-on-one mentorship to learners, addressing individual doubts and helping them troubleshoot complex problems. Monitor learners progress, provide constructive feedback, and suggest improvement strategies. Assessment and Evaluation: Develop and administer assessments to evaluate learners understanding and skill levels. Analyze test results and provide detailed performance feedback. Domain-Specific Expertise: Explain and demonstrate key AI/ML concepts, such as supervised and unsupervised learning, reinforcement learning, natural language processing (NLP), and computer vision techniques. Guide learners in working with large language models (LLMs) like GPT and BERT, focusing on fine-tuning and deployment. Train learners on deep learning topics, including neural networks, CNNs, RNNs, and transformers. Stay Updated on Trends: Continuously research advancements in AI, ML, Deep Learning, and Python, incorporating cutting-edge techniques into the training materials. Maintain familiarity with emerging technologies like generative AI and explainable AI. Soft Skills and Collaboration: Communicate complex concepts clearly to learners from diverse technical and non-technical backgrounds. Foster an engaging and interactive learning environment, encouraging collaboration among participants. What We Offer Be part of cutting-edge AI projects and work on real-world applications of Machine Learning, Deep Learning, Large Language Models (LLMs), and Computer Vision. Opportunity to stay ahead in the AI revolution by working with the latest tools and technologies like TensorFlow, PyTorch, OpenCV, and Hugging Face. Access to continuous learning resources and mentorship programs to sharpen your expertise and stay updated with emerging trends. Build leadership and communication skills by mentoring learners and engaging with professionals across various industries. Connect with industry experts, aspiring AI professionals, and innovators, giving you a strong professional network. Grow with the company! Be part of our exciting journey as we expand and make an impact in the AI training industry. Enjoy early access to leadership opportunities and the chance to shape the companys future direction. Our Culture & Values Startup Culture - Fast-Paced, Collaborative, and Innovative A place for growth. We believe in nurturing talent and giving everyone the chance to grow professionally and personally We work as a team, supporting and learning from each other. Every voice matters here We trust our team to take ownership of their work and make meaningful contributions. Dynamic startup energy Collaborative leadership Continuous learning

Proficiency in Python, LangChain, LangGraph and GenAI APIs. Hands-on experience with vector databases (Pinecone, FAISS, ChromaDB). Understanding of Agentic AI, LLMs, transformers, and orchestration frameworks. Exposure to cloud services (AWS/GCP/Azure) and CI/CD practices. Stay current with AI trends and toolsSourcing & Screening US profiles.

Experience inimplementing & designing data pipelines using Azure Data Factory Advanced knowledge of Azure Functions,Event Grid Data processing using Azure AI services,cognitive services,Azure cognitive search Stakeholder management,project management

We have an excellent opportunity with one of our prestigious clients for CMMI Level 5 Company Skills - Large Language Models Exp- 13 Years to 25 Years Locations - Pan India Candidate must have 15 years of regular education. Must have Relevant experience minimum 8 Years of Exp in Large Language Models with Machine Learning, Natural Language Processing (NLP), Deep Learning, GenAI , MLOps , Python, AWS, Azure, GCP . Kindly share below the following details as well . Full Name: Total experience: Relevant Experience: Current CTC: Expected CTC: Notice Period: Current location: Preferred Location: As an AI/ML Engineer, you will develop applications and systems utilizing AI tools, Cloud AI services, and GenAI models. Your role involves creating cloud or on-prem application pipelines with production-ready quality, incorporating deep learning, neural networks, chatbots, and image processing. Must Have Skills : Proficiency in Large Language Models. Strong understanding of deep learning frameworks such as TensorFlow or PyTorch, Machine Learning, Natural Language Processing (NLP), Deep Learning ,GenAI,MLOps ,Python. Experience with cloud platforms like AWS, Azure, or Google Cloud for deploying AI solutions. Thanks Anand anand@vuiinfotech.in

Role & responsibilities • Familiarity with Mainframe and Midrange platforms is essential for integrating Gen AI solutions into legacy enterprise systems. Candidate should understand data structures, interfaces, and operational workflows on platforms like IBM Z(Mainframe) and IBM I (Midrange). Experience in modernizing and bridging AI applications with these systems is a strong advantage. masters or PhD in Computer Science, Machine Learning, or related field (or equivalent experience) 5+ years in AI/ML development, with 3+ years focused on generative AI (LLMs, GANs, VAEs, etc.) Proven track record of deploying generative AI solutions in production environments mandatory technical skills: deep expertise in generative architectures (GPT, Transformers, Diffusion Models) Experience with NLP tools (Hugging Face, spaCy) and vector databases (Pinecone, FAISS) mandatory proficiency in Python, PyTorch/TensorFlow, and cloud platforms preferred: knowledge of multimodal AI (text-to-image, video synthesis) experience with reinforcement learning (RLHF) for model alignment preferred familiarity with AI ethics frameworks (e.g., AI Fairness 360) strong analytical and problem-solving skills, excellent communication and collaboration abilities, attention to detail and ability to work independently Interested candidate can share me resume in recruiter.wtr26@walikingtree.in

Job Title : AI Engineer Location: Chennai Experience: 5+ Years (Hands-On Data Science & AI) Employment Type: Full-Time Work type - Work from office. About the Role We are seeking a skilled AI Engineer with deep hands-on experience in ML, NLP, LLMs, GenAI, and Agentic AI to join our technology team focused on automating US mortgage loan processing workflows. This role involves designing intelligent, scalable solutions using cloud-native MLOps and advanced AI/LLM orchestration tools on Azure. Key Responsibilities Design and implement ML/NLP/GenAI pipelines for automating loan origination, underwriting, and document intelligence processes. Develop and deploy LLM-based solutions using tools like Ollama, OpenAI, HuggingFace, and integrate via LangChain or similar frameworks. Build and orchestrate Agentic AI systems (e.g., using LangChain Agents, AutoGen, CrewAI) to enable autonomous decision-making, task planning, and loan-processing agents. Fine-tune domain-specific LLMs and embeddings for intelligent document classification, summarization, and question answering. Develop end-to-end MLOps workflows for scalable training, testing, and monitoring of models. Deploy AI models and microservices using Azure (Azure ML, Functions, Blob Storage, App Services). Work with cross-functional teams to ensure compliance, explainability, and effectiveness of AI solutions. Leverage prompt engineering, RAG (Retrieval-Augmented Generation), and vector stores for contextual mortgage document workflows. Required Skills & Qualifications 5+ years of hands-on experience in Machine Learning, NLP, or LLM-based systems. Proven expertise with LLMs (e.g., OpenAI, Ollama, GPT-4, Mistral) and LangChain / AutoGen / Agentic AI design. Proficiency in Python, Scikit-learn, PyTorch/TensorFlow, Spacy, HuggingFace Transformers. Strong knowledge of Azure Cloud including Azure ML, Azure Functions, Azure DevOps. Experience with MLOps tools like MLflow, Azure ML pipelines, or Kubeflow. Familiarity with vector databases (e.g., FAISS, Pinecone, Weaviate). Experience deploying models into production-scale environments. Nice to Have Understanding of US mortgage or lending workflows (1003, 1008, bank statements, etc.). Experience with OCR, document intelligence tools (Azure Form Recognizer, Amazon Textract). Exposure to Agentic AI concepts such as autonomous agents, planning, memory chaining. Knowledge of privacy and compliance frameworks (HIPAA, SOC2) in AI deployments. What We Offer Opportunity to lead GenAI and Agentic AI initiatives for mortgage automation. Access to top-tier tools, frameworks, and cloud platforms. Remote flexibility and career growth in an innovation-first team. Impactful work transforming legacy loan operations through AI. Interested candidates kindly share your resume to SGrace@ca-usa.com.

* Design, develop & maintain Python applications using Langchain & LLMS. * Optimize database performance with PostgreSQL & MySQL. Implement and integrate Retrieval-Augmented Generation (RAG) pipelines using LLMs Provident fund Health insurance

About this role: Wells Fargo is seeking a Principal Engineer to drive the design, development, and implementation of Artificial Intelligence (AI) enabled applications aligned to employee-facing lines of business in Enterprise Functions Technology (EFT). The EFT AI team will focus on building intelligent, efficient, and user-centric tools to accelerate the work of users in Finance, Human Resources, Risk, Audit, Legal, Public Affairs, Diverse Segments and EFT Platform Technology. In addition to hands-on development, this role will play a key part in evolving the AI operating model for both horizontal (cross product/platform) and vertical support (product specific). As a key technical contributor, you will collaborate with cross-functional teams to align solutions with the mission of transforming the Wells Fargo employee experience. This role will be a key contributor to shaping AI infrastructure, governance, and automation frameworks, working closely with cross-functional partners in technology, product management, and operations. The horizontal focus of this role will support AI platform scalability, reliability and AI governance, ensuring alignment across EFT, while the vertical focus will support specific applications and their integration within business domains. The successful candidate will have a deep expertise in AI engineering, cloud-based AI deployment, and AI model lifecycle management, along with experience in architecting AI solutions that align with responsible principles and enterprise business objectives. This is a unique opportunity to lead AI engineering efforts while shaping the AI operating model. In this role, you will: Design, develop and optimize Gen AI applications using agentic frameworks and tools Accelerate end to end solution delivery timelines by developing automated data, prompting and evaluation pipelines Streamline the enablement of AI solutions by building solution blueprints, re-usable patterns and identifying process improvements Lead AI engineering efforts that drive the design, development, scalability, and evolution of AI-powered products, ensuring AI adoption. Research and guide engineering efforts to solve complex engineering challenges and balance accuracy, latency and cost Evolve the AI operating model, ensuring seamless integration of AI solutions into business domains while providing horizontal AI governance and infrastructure support. Develop automated AI model monitoring frameworks, enabling continuous model updates, explainability, and performance tracking. Develop and scale AI platforms leveraging Large Language Model (LLM) services, real time analytics, AI automation, and intelligent decision-making. Act as an advisor and collaborate with leadership to integrate AI into existing enterprise systems and cloud platforms to implement innovative and significant business solutions. Drive cross-functional collaboration to define AI roadmaps, infrastructure strategies, and product enhancements, ensuring AI capabilities align with business AI strategies. Lead the strategy and resolution of highly complex and unique challenges requiring in-depth evaluation across multiple areas or the enterprise, delivering solutions that require vision, creativity, innovation, and advanced analytical and thinking. Maintain knowledge of industry best practices and new technologies and recommend innovations that enhance operations or provide a competitive advantage to the organization. Strategically engage with all levels of professionals and managers across the enterprise and serve as an expert advisor to leadership. Responsible for meticulous governance to address the unique risks posed by GenAI. Required Qualifications: 7+ years of Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education 7+ years of engineering experience building and supporting large scale customer facing products using modern technologies 3+ years building and delivering products using AI technologies. Desired Qualifications: Strong expertise in AI model development and deployment with a strong background in LLMs, generative AI, and AI-engineering. Deep experience with generative AI models, including model prompting, tuning, and safety best practices. Expertise in solution architecture and applying modular design techniques to agentic workflows Solid grasp of data and error analysis, identifying issues and patterns throughout the AI pipeline Strong expertise in test or eval driven development, ensuring robust and scalable AI software. Experience in backend application software development, with ability to quickly adapt to C#, and Python code bases. Strong understanding of Retrieval-Augmented Generation (RAG), knowledge graphs and agentic workflows. Deep knowledge of AI infrastructure, Generative AI Operations, and enterprise-scale AI adoption strategies. Familiarity with enterprise-scale software systems and their integration within large organizations. Passion for building AI solutions that deliver a seamless, end-user-focused experience. Experience in enterprise AI model lifecycle management, AI compliance, and risk mitigation strategies. Strong understanding of human centered AI design for workplace applications. Excellent collaboration, communication, and problem-solving skills. Job Expectations: Lead projects, teams, and serve as a peer mentor. Be Humble: You're smart yet always interested in learning from others Work Transparently: You always deal in an honest, direct, and transparent way. Take Ownership: You embrace responsibility and find joy in having the answers Learn More: You regularly self-educate and improve your skill set. Show Gratitude: You show appreciation and respect to those you work with.

Role & responsibilities Develop, test, and maintain backend services using Python and frameworks such as FastAPI or Flask . Implement and optimize LLM-based applications using models like OpenAI (GPT-4o) , Gemini , LLaMA , etc. Work on RAG implementations , including integration with vector databases and prompt engineering strategies. Design, build, and maintain database connectivity using SQL for infrastructure-level applications. Develop and deploy containerized applications using Docker , Git , GitHub , and integrate with CI/CD pipelines . Deploy and manage applications on cloud platforms ( AWS , Azure , GCP ). Ensure clean code practices including unit testing , error handling , Python best practices , and design patterns . Collaborate with cross-functional teams including Product, Data Science, and DevOps for end-to-end solution delivery. Preferred candidate profile Strong proficiency in Python programming . Familiarity with FastAPI , Flask , or similar web frameworks. Experience with SQL databases and connection management. Hands-on with LLMs and RAG workflows (OpenAI GPT, Gemini, LLaMA, etc.). Understanding of vector databases such as FAISS, Pinecone, or similar. Proficiency with Git , GitHub , and CI/CD pipelines . Experience with Docker for containerization. Exposure to any of the major cloud platforms AWS , Azure , or GCP . Ability to write unit test cases , implement robust error handling , and follow design patterns . Clear understanding of enterprise software development best practices . Someone who have experience working with Banking or Financial Services projects/clients. Immediate Joiner or someone serving notice period.

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.

Job Title: Generative AI Specialist Experience: Total 7+ Years | Relevant - 3 to 5 Years Location: Hyderabad Employment Type: Full-Time Job Description We are seeking a highly skilled and innovative Generative AI Engineer to join our team. The ideal candidate will have a strong background in designing, developing, and deploying AI models, particularly in the domain of generative AI and large language models (LLMs). Key Responsibilities Design & Development: Architect and build generative AI models, algorithms, and frameworks. Model Implementation: Integrate AI models into existing systems and applications. LLM Expertise: Work with tools like LangChain, Haystack, and apply prompt engineering techniques. Data Handling: Preprocess and analyze data for model training and evaluation. Cross-functional Collaboration: Partner with data scientists, product managers, and other stakeholders. Testing & Deployment: Evaluate model performance and deploy models to production. Monitoring & Optimization: Track model performance and continuously improve results. Research & Innovation: Stay updated with the latest advancements in generative AI. Required Skills Proficiency in Python for AI development. Strong understanding of Generative AI , NLP , and LLMs . Experience with RAG pipelines and vector databases . Familiarity with frameworks like LangChain , Haystack , and other open-source libraries. Knowledge of prompt engineering and tokenization . Experience in fine-tuning and integrating AI models in production. Excellent communication and problem-solving skills. Optional Skills Experience with cloud platforms (GCP, AWS, Azure). Familiarity with MLOps and DevOps practices. Why Join Us? Work on cutting-edge AI technologies. Collaborate with a passionate and talented team. Opportunity to innovate and shape the future of AI applications. How to Apply Interested candidates can apply directly through Naukri or send your updated resume to shilpa.shapur@Excelra.com

About the Team and Our Scope We are a forward-thinking tech organization within Swiss Re, delivering transformative AI/ML solutions that redefine how businesses operate. Our mission is to build intelligent, secure, and scalable systems that deliver real-time insights, automation, and high-impact user experiences to clients globally. You'll join a high-velocity AI/ML team working closely with product managers, architects, and engineers to create next-gen enterprise-grade solutions. Our team is built on a startup mindset - bias to action, fast iterations, and ruthless focus on value delivery. We're not only shaping the future of AI in business - we're shaping the future of talent. This role is ideal for someone passionate about advanced AI engineering today and curious about evolving into a product leadership role tomorrow. You'll get exposure to customer discovery, roadmap planning, and strategic decision-making alongside your technical contributions. Role Overview As an AI/ML Engineer, you will play a pivotal role in the research, development, and deployment of next-generation GenAI and machine learning solutions . Your scope will go beyond retrieval-augmented generation (RAG) to include areas such as prompt engineering, long-context LLM orchestration, multi-modal model integration (voice, text, image, PDF), and agent-based workflows. You will help assess trade-offs between RAG and context-native strategies, explore hybrid techniques, and build intelligent pipelines that blend structured and unstructured data. You'll work with technologies such as LLMs, vector databases, orchestration frameworks, prompt chaining libraries, and embedding models, embedding intelligence into complex, business-critical systems. This role sits at the intersection of rapid GenAI prototyping and rigorous enterprise deployment, giving you hands-on influence over both the technical stack and the emerging product direction. Key Responsibilities Build Next-Gen GenAI Pipelines : Design, implement, and optimize pipelines across RAG, prompt engineering, long-context input handling, and multi-modal processing. Prototype, Validate, Deploy : Rapidly test ideas through PoCs, validate performance against real-world business use cases, and industrialize successful patterns. Ingest, Enrich, Embed: Construct ingestion workflows including OCR, chunking, embeddings, and indexing into vector databases to unlock unstructured data. Integrate Seamlessly: Embed GenAI services into critical business workflows, balancing scalability, compliance, latency, and observability. Explore Hybrid Strategies: Combine RAG with context-native models, retrieval mechanisms, and agentic reasoning to build robust hybrid architectures. Drive Impact with Product Thinking : Collaborate with product managers and UX designers to shape user-centric solutions and understand business context. Ensure Enterprise-Grade Quality: Deliver solutions that are secure, compliant (e.g., GDPR), explainable, and resilient - especially in regulated environments. What Makes You a Fit Must-Have Technical Expertise Proven experience with GenAI techniques and LLMs , including RAG, long-context inference, prompt tuning, and multi-modal integration. Strong hands-on skills with Python , embedding models, and orchestration libraries (e.g., LangChain, Semantic Kernel, or equivalents). Comfort with MLOps practices , including version control, CI/CD pipelines, model monitoring, and reproducibility. Ability to operate independently, deliver iteratively, and challenge assumptions with data-driven insight. Understanding of vector search optimization and retrieval tuning. Exposure to multi-modal models Nice-To-Have Qualifications Experience building and operating AI systems in regulated industries (e.g., insurance, finance, healthcare). Familiarity with Azure AI ecosystem (e.g., Azure OpenAI, Azure AI Document Intelligence, Azure Cognitive Search) and deployment practices in cloud-native environments. Experience with agentic AI architectures , tools like AutoGen, or prompt chaining frameworks. Familiarity with data privacy and auditability principles in enterprise AI. Bonus: You Think Like a Product Manager While this role is technical at its core, we highly value candidates who are curious about how AI features become products . If you're excited by the idea of influencing roadmaps, shaping requirements, or owning end-to-end value delivery - we'll give you space to grow into it. This is a role where engineering and product are not silos . If you're keen to move in that direction, we'll mentor and support your evolution. Why Join Us You'll be part of a team that's pushing AI/ML into uncharted, high-value territory. We operate with urgency, autonomy, and deep collaboration. You'll prototype fast, deliver often, and see your work shape real-world outcomes - whether in underwriting, claims, or data orchestration. And if you're looking to transition from deep tech to product leadership , this role is a launchpad. Swiss Re is an equal opportunity employer . We celebrate diversity and are committed to creating an inclusive environment for all employees. Keywords: Reference Code: 134317

Job Description Summary role description: Hiring for a Solution Architect for an InsurTech platform provider, Life and Health Insurance. Company description: Our client is a VC-funded InsurTech platform company, providing software platforms for Life Insurance and Health Insurance companies across the globe. Leveraging their domain expertise, regulatory knowledge and technology experience, they architect innovative products and disrupt the Insurance value chain from Customer Acquisition to Engagement. Their products serve customers across the APAC region. Role details: Title / Designation : Solutions Architect Location: Pune/Mumbai Work Mode: Work from office Role & responsibilities: Define and evolve AI/ML architecture roadmap for FWA, IDP, and Agentic AI frameworks. Lead technical presentations and solution design sessions with customers. Design scalable architectures for multi-agent systems and autonomous decision-making. Drive innovation by evaluating emerging AI/ML technologies, especially AI agents. Architect cloud-native platforms supporting the complete AI/ML lifecycle. Provide technical leadership across product development and customer implementation. Collaborate with data scientists, engineers, and business stakeholders. Stay at the forefront of AI/ML innovations, particularly autonomous agents and LLMs. Establish and enforce technical standards and architectural guidelines. Candidate requirements: 10+ years in software architecture/system design in insurance domain, with 5+ years in AI/ML systems/platforms. Proven experience delivering large-scale AI/ML solutions, preferably with autonomous agents. Experience with cloud-native architectures (AWS, Azure, GCP), containerization (Docker, Kubernetes), and microservices. Deep expertise in AI/ML system architecture (model serving, MLOps/LLMOps pipelines, distributed computing). Strong understanding of Agentic AI, multi-agent systems, and LLMs (including LoRA, PEFT fine-tuning). Bachelor's or Master's in CS, SE, Data Science, or related technical field. Exceptional technical leadership and communication skills. Selection process: Interview with Senior Solution Architect Interview with CTO HR Discussion Check Your Resume for Match Upload your resume and our tool will compare it to the requirements for this job like recruiters do.

Key Responsibilities: LLM Integration & Development: Build and fine-tune LLMs for task-specific applications using techniques like prompt engineering, retrieval-augmented generation (RAG), fine-tuning, and model adaptation. AI Agent Engineering: Design, develop, and orchestrate AI agents capable of reasoning, planning, tool use (e.g., APIs, plugins), and autonomous execution for user-defined goals. GenAI Use Case Implementation: Deliver GenAI-powered solutions such as chatbots, summarizers, document Q&A systems, assistants, and co-pilot tools using frameworks like LangChain or LlamaIndex. System Integration: Connect LLM-based agents to external tools, APIs, databases, and knowledge sources for real-time, contextualized task execution. Performance Tuning: Optimize model performance, cost-efficiency, safety, and latency using caching, batching, evaluation tools, and monitoring systems. Collaboration & Documentation: Work closely with AI researchers, product teams, and engineers to iterate quickly. Maintain well-structured, reusable, and documented codebases. Required Qualifications: 35 years of experience in AI/ML, with at least 12 years hands-on with GenAI or LLMs. Strong Python development skills and experience with ML frameworks (e.g., Hugging Face, LangChain, OpenAI API, Transformers). Familiarity with LLM orchestration, vector databases (e.g., FAISS, Pinecone, Weaviate), and embedding models. Understanding of prompt engineering, agent architectures, and conversational AI flows. Bachelor's or Master's degree in Computer Science, Artificial Intelligence, or related field. Preferred Qualifications: Experience deploying AI systems in cloud environments (AWS/GCP/Azure) or with containerized setups (Docker/Kubernetes). Familiarity with open-source LLMs (LLaMA, Mistral, Mixtral, etc.) and open-weight tuning methods (LoRA, QLoRA). Exposure to RAG pipelines, autonomous agents (e.g., Auto-GPT, BabyAGI), and multi-agent systems. Knowledge of model safety, evaluation, and compliance standards in GenAI.

Key Responsibilities: LLM Integration & Development: Build and fine-tune LLMs for task-specific applications using techniques like prompt engineering, retrieval-augmented generation (RAG), fine-tuning, and model adaptation. AI Agent Engineering: Design, develop, and orchestrate AI agents capable of reasoning, planning, tool use (e.g., APIs, plugins), and autonomous execution for user-defined goals. GenAI Use Case Implementation: Deliver GenAI-powered solutions such as chatbots, summarizers, document Q&A systems, assistants, and co-pilot tools using frameworks like LangChain or LlamaIndex. System Integration: Connect LLM-based agents to external tools, APIs, databases, and knowledge sources for real-time, contextualized task execution. Performance Tuning: Optimize model performance, cost-efficiency, safety, and latency using caching, batching, evaluation tools, and monitoring systems. Collaboration & Documentation: Work closely with AI researchers, product teams, and engineers to iterate quickly. Maintain well-structured, reusable, and documented codebases. Required Qualifications: 35 years of experience in AI/ML, with at least 12 years hands-on with GenAI or LLMs. Strong Python development skills and experience with ML frameworks (e.g., Hugging Face, LangChain, OpenAI API, Transformers). Familiarity with LLM orchestration, vector databases (e.g., FAISS, Pinecone, Weaviate), and embedding models. Understanding of prompt engineering, agent architectures, and conversational AI flows. Bachelor's or Master's degree in Computer Science, Artificial Intelligence, or related field. Preferred Qualifications: Experience deploying AI systems in cloud environments (AWS/GCP/Azure) or with containerized setups (Docker/Kubernetes). Familiarity with open-source LLMs (LLaMA, Mistral, Mixtral, etc.) and open-weight tuning methods (LoRA, QLoRA). Exposure to RAG pipelines, autonomous agents (e.g., Auto-GPT, BabyAGI), and multi-agent systems. Knowledge of model safety, evaluation, and compliance standards in GenAI.

Key Responsibilities: LLM Integration & Development: Build and fine-tune LLMs for task-specific applications using techniques like prompt engineering, retrieval-augmented generation (RAG), fine-tuning, and model adaptation. AI Agent Engineering: Design, develop, and orchestrate AI agents capable of reasoning, planning, tool use (e.g., APIs, plugins), and autonomous execution for user-defined goals. GenAI Use Case Implementation: Deliver GenAI-powered solutions such as chatbots, summarizers, document Q&A systems, assistants, and co-pilot tools using frameworks like LangChain or LlamaIndex. System Integration: Connect LLM-based agents to external tools, APIs, databases, and knowledge sources for real-time, contextualized task execution. Performance Tuning: Optimize model performance, cost-efficiency, safety, and latency using caching, batching, evaluation tools, and monitoring systems. Collaboration & Documentation: Work closely with AI researchers, product teams, and engineers to iterate quickly. Maintain well-structured, reusable, and documented codebases. Required Qualifications: 35 years of experience in AI/ML, with at least 12 years hands-on with GenAI or LLMs. Strong Python development skills and experience with ML frameworks (e.g., Hugging Face, LangChain, OpenAI API, Transformers). Familiarity with LLM orchestration, vector databases (e.g., FAISS, Pinecone, Weaviate), and embedding models. Understanding of prompt engineering, agent architectures, and conversational AI flows. Bachelor's or Master's degree in Computer Science, Artificial Intelligence, or related field. Preferred Qualifications: Experience deploying AI systems in cloud environments (AWS/GCP/Azure) or with containerized setups (Docker/Kubernetes). Familiarity with open-source LLMs (LLaMA, Mistral, Mixtral, etc.) and open-weight tuning methods (LoRA, QLoRA). Exposure to RAG pipelines, autonomous agents (e.g., Auto-GPT, BabyAGI), and multi-agent systems. Knowledge of model safety, evaluation, and compliance standards in GenAI.