5 Llm Applications Jobs

Ready to build the future with AI At Genpact, we don&rsquot just keep up with technology&mdashwe set the pace. AI and digital innovation are redefining industries, and we&rsquore leading the charge. Genpact&rsquos AI Gigafactory, our industry-first accelerator, is an example of how we&rsquore scaling advanced technology solutions to help global enterprises work smarter, grow faster, and transform at scale. From large-scale models to agentic AI, our breakthrough solutions tackle companies most complex challenges. If you thrive in a fast-moving, innovation-driven environment, love building and deploying cutting-edge AI solutions, and want to push the boundaries of what&rsquos possible, this is your moment. Genpact (NYSE: G) is an advanced technology services and solutions company that delivers lasting value for leading enterprises globally. Through our deep business knowledge, operational excellence, and cutting-edge solutions - we help companies across industries get ahead and stay ahead. Powered by curiosity, courage, and innovation, our teams implement data, technology, and AI to create tomorrow, today. Get to know us at genpact.com and on LinkedIn, X, YouTube, and Facebook. Inviting applications for the role of Lead Consultant - AI/ML We are looking for experienced offshore resource Responsibilities . Deploy and maintain knowledge ingestion pipelines and integration into API-based services. . Strong knowledge of data cleansing, NLP, parsing tools, regex, and optimization strategies for RAG. . Experience fine-tuning and deploying LLMs. . Stay current on the latest GenAI trends, frameworks, and coding practices. . Experience programming with Python. . Experience in Git and version control. . Experience with a public cloud ( . Experience in using Scikit-learn . Langchain experience. . LLM experience building RAG systems . Year experience with vector databases such as MongoDB Atlas or Pinecone . Portfolio of LLM applications and sample projects . NLP experience using tools such as NLTK, SpaCy, and Beautiful soup . LLM experience building RAG systems at scale (10,000+ documents). . Experience in DevOps with Github Actions or similar CI/CD tools. . Experience of writing and deploying microservices . Kubernetes experience . Strong code refactoring skills . Strong debugging skills. . Familiarity with concepts such as Agents, adding memory to LLMs, routing, moderating content, parsing output Qualifications we seek in you! Minimum Qualifications . Solid understanding of data quality testing principles and practices. . Hands on experience in an agile development environment. . Strong problem-solving skills and the ability to troubleshoot complex issues. . Excellent communications skills and ability to work effectively in a fast-paced, team-oriented environment. Preferred Qualifications/ Skills . Excellent analytical and problem-solving skills, with a keen attention to detail. . Effective communication and interpersonal skills, with the ability to collaborate effectively with cross-functional teams and stakeholders. . Experience with a public cloud ( . Experience in using Scikit-learn . Langchain experience. . LLM experience building RAG systems . Year experience with vector databases such as MongoDB Atlas or Pinecone . Portfolio of LLM applications and sample projects . NLP experience using tools such as NLTK, SpaCy, and Beautiful soup . LLM experience building RAG systems at scale (10,000+ documents). . Experience in DevOps with Github Actions or similar CI/CD tools. . Experience of writing and deploying microservices . Kubernetes experience . Strong code refactoring skills . Strong debugging skills. . Familiarity with concepts such as Agents, adding memory to LLMs, routing, moderating content, parsing output Why join Genpact . Lead AI-first transformation - Build and scale AI solutions that redefine industries . Make an impact - Drive change for global enterprises and solve business challenges that matter . Accelerate your career&mdashGain hands-on experience, world-class training, mentorship, and AI certifications to advance your skills . Grow with the best - Learn from top engineers, data scientists, and AI experts in a dynamic, fast-moving workplace . Committed to ethical AI - Work in an environment where governance, transparency, and security are at the core of everything we build . Thrive in a values-driven culture - Our courage, curiosity, and incisiveness - built on a foundation of integrity and inclusion - allow your ideas to fuel progress Come join the 140,000+ coders, tech shapers, and growth makers at Genpact and take your career in the only direction that matters: Up. Let&rsquos build tomorrow together. 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. 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.

Job Summary: We are seeking a highly skilled MLOps Engineer to design, deploy, and manage machine learning pipelines in Google Cloud Platform (GCP). In this role, you will be responsible for automating ML workflows, optimizing model deployment, ensuring model reliability, and implementing CI/CD pipelines for ML systems. You will work with Vertex AI, Kubernetes (GKE), BigQuery, and Terraform to build scalable and cost-efficient ML infrastructure. The ideal candidate must have a good understanding of ML algorithms, experience in model monitoring, performance optimization, Looker dashboards and infrastructure as code (IaC), ensuring ML models are production-ready, reliable, and continuously improving. You will be interacting with multiple technical teams, including architects and business stakeholders to develop state of the art machine learning systems that create value for the business. Responsibilities: Managing the deployment and maintenance of machine learning models in production environments and ensuring seamless integration with existing systems. Monitoring model performance using metrics such as accuracy, precision, recall, and F1 score, and addressing issues like performance degradation, drift, or bias. Troubleshoot and resolve problems, maintain documentation, and manage model versions for audit and rollback. Analyzing monitoring data to preemptively identify potential issues and providing regular performance reports to stakeholders. Optimization of the queries and pipelines. Modernization of the applications whenever required Qualifications: Expertise in programming languages like Python, SQL Solid understanding of best MLOps practices and concepts for deploying enterprise level ML systems. Understanding of Machine Learning concepts, models and algorithms including traditional regression, clustering models and neural networks (including deep learning, transformers, etc.) Understanding of model evaluation metrics, model monitoring tools and practices. Experienced with GCP tools like BigQueryML, MLOPS, Vertex AI Pipelines (Kubeflow Pipelines on GCP), Model Versioning & Registry, Cloud Monitoring, Kubernetes, etc. Solid oral and written communication skills and ability to prepare detailed technical documentation of new and existing applications. Strong ownership and collaborative qualities in their domain. Takes initiative to identify and drive opportunities for improvement and process streamlining. Bachelors Degree in a quantitative field of mathematics, computer science, physics, economics, engineering, statistics (operations research, quantitative social science, etc.), international equivalent, or equivalent job experience. Bonus Qualifications: Experience in Azure MLOPS, Familiarity with Cloud Billing. Experience in setting up or supporting NLP, Gen AI, LLM applications with MLOps features. Experience working in an Agile environment, understanding of Lean Agile principles.

ExperienceRequired: 8-10 years PositionType: Contract WorkMode: Remote,Delhi NCR,Bengaluru,Chennai,Pune,Kolkata,Ahmedabad, Mumbai, Hyderabad ShiftTiming: Flexible can start between 11 AM to 2 PM IST, end between 8 PM to 11 PM IST 3MustSkills: Gen AI, AWS, SQL Key Responsibilities NLP Expertise: Strong foundation in NLP methods text classification, sentiment detection, entity recognition. RAG Expertise: Proficiency with Retrieval-Augmented Generation (RAG); experience with vector databases (Weaviate, Pinecone). LLM Applications: At least 1 year experience building LLM-based applications using 3rd-party models (OpenAI, Anthropic). Prompt Engineering: Skilled in prompt engineering, crafting function calls, building conversational AI apps. Advanced LLM Techniques: Familiarity with zero-shot, few-shot learning, and fine-tuning. Python Programming: Extensive Python programming expertise to implement complex solutions. GenAI Libraries: Experience with Langchain, HuggingFace. Version Control: Proficient with Git and collaborative workflows. Data Preparation: Manage large structured & unstructured datasets. ML Deployment: Deploy, scale, and monitor ML/LLM models in live environments. Collaboration: Occasional overlap with US Eastern Time for team collaboration. DesiredExperience OpenSourceLLMs: Experience with frameworks like Llama or Mistral. RegulatedSectorExperience: Prior experience with data in regulated sectors (Healthcare, Banking). TechnicalSkillsAndCapabilities APIDevelopment: RESTful API design & development (Python-FastAPI). JavaScriptExpertise: Frontend & backend development using JavaScript + frameworks. Microservices Architecture: Architect scalable microservices-based solutions. GenerativeAILandscape: Deep understanding of RAG, vector embeddings, LLMs, OSS AI tools. CloudPlatforms: AWS / Azure / GCP deep understanding of cloud data services. DatabaseExpertise: SQL & NoSQL database design and optimization. DataStreaming: Kafka / Azure Event Hub / AWS Kinesis experience. AgilePractices: Experience with Agile development, Git, Jenkins, Azure DevOps. CICDPipelines: Ability to build/manage CI/CD pipelines. CommunicationSkills: Strong team collaboration, technical & non-technical stakeholder engagement.

About this role: Wells Fargo is seeking a Software Engineer. In this role, you will: Participate in low to moderately complex initiatives and projects associated with the technology domain, including installation, upgrades, and deployment efforts Identify opportunities for service quality and availability improvements within the technology domain environment Design, code, test, debug, and document for low to moderately complex projects and programs associated with technology domain, including upgrades and deployments Review and analyze technical assignments or challenges that are related to low to medium risk deliverables and that require research, evaluation, and selection of alternative technology domains Present recommendations for resolving issues or may escalate issues as needed to meet established service level agreements Exercise some independent judgment while also developing understanding of given technology domain in reference to security and compliance requirements Provide information to technology colleagues, internal partners, and stakeholders Required Qualifications: 2+ years of software engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education Desired Qualifications: Work as a Generative AI engineer developing enterprise-scale AI applications Design, implement, and optimize LLM-based solutions using state-of-the-art frameworks Lead Gen AI initiatives focused on developing intelligent agents and conversational systems Design and build robust LLM interfaces and orchestration pipelines Develop evaluation frameworks to measure and improve model performance Implement prompt engineering techniques to optimize model outputs Integrate Gen AI capabilities with existing enterprise applications Build and maintain frontend interfaces for AI applications Strong proficiency in Python/Java and LLM orchestration frameworks (LangChain, LangGraph) Basic Knowledge of model context protocols, RAG architectures, and embedding techniques Experience with model evaluation frameworks and metrics for LLM performance Proficiency in frontend development with React.js for AI applications Experience with UI/UX design patterns specific to AI interfaces Experience with vector databases and efficient retrieval methods Knowledge of prompt engineering techniques and best practices Experience with containerization and microservices architecture Strong understanding of semantic search and document retrieval systems Working knowledge of both structured and unstructured data processing Experience with version control using GitHub and CI/CD pipelines Experience working with globally distributed teams in Agile scrums Job Expectations: Understanding of enterprise use cases for Generative AI Knowledge of responsible AI practices and ethical considerations Ability to optimize AI solutions for performance and cost Well versed in MLOps concepts for LLM applications Staying current with rapidly evolving Gen AI technologies and best practices Experience implementing security best practices for AI applications

ZENSAR - OPPORTUNITY FOR Gen AI with Python Engineer” Apply Here: - https://forms.office.com/r/nVP0Mg5eeE Dear Aspirant, Greetings from Zensar!! We are thrilled to offer you an excellent opportunity to join our team as a Gen AI with Python Engineer professional . Experience Required: 6 - 9 Years Location: Pune, Bangalore, Chennai, Hyderabad (Hybrid) LLM Applications & Agentic Frameworks Design and implement end-to-end LLM applications using OpenAI, Claude, Mistral, Gemini, or LLaMA on AWS, Databricks, Azure or GCP. Build intelligent, autonomous agents using LangGraph, AutoGen, LlamaIndex, Crew.ai, or custom frameworks. Develop Multi Model, Multi Agent, Retrieval-Augmented Generation (RAG) applications with secure context embedding and tracing with reports. Rapidly explore and showcase the art of the possible through functional, demonstrable POCs Advanced AI Experimentation Fine-tune LLMs and Small Language Models (SLMs) for domain-specific use. Create and leverage synthetic datasets to simulate edge cases and scale training. Evaluate agents using custom agent evaluation frameworks (success rates, latency, reliability) Evaluate emerging agent communication standards — A2A (Agent-to-Agent) and MCP (Model Context Protocol) Business Alignment & Cross-Team Collaboration Translate ambiguous requirements into structured, AI-enabled solutions. Clearly communicate and present ideas, outcomes, and system behaviors to technical and non-technical stakeholders Good-To-Have Microsoft Copilot Studio DevRev Codium Cursor Atlassian AI Databricks Mosaic AI Qualifications 6–9 years of experience in software development or AI/ML engineering At least 3 years working with LLMs, GenAI applications, or agentic frameworks. Proficient in AI/ML, MLOps concepts, Python, embeddings, prompt engineering, and model orchestration Proven track record of developing functional AI prototypes beyond notebooks. Strong presentation and storytelling skills to clearly convey GenAI concepts and value. Ability to independently drive AI experiments from ideation to working demo. Role & responsibilities Preferred candidate profile