Ai Ml Engineer
- Capgemini
- 4 - 9 years
- Bengaluru
- 4 days ago
- Email to a friend
- Report this job
Job Description
Job Description: AI/ML Engineer Agentic AI & Intelligent Systems
Position Overview
We are seeking an experienced AI/ML Engineer to design, develop, and deploy intelligent agentic systems that go beyond traditional retrieval-augmented generation (RAG) pipelines. The ideal candidate will build multi-step reasoning agents capable of autonomously planning, selecting tools, and executing complex tasks integrating LLM capabilities with enterprise data sources, SQL databases, knowledge graphs, and cloud-native infrastructure.
Key Responsibilities
AI/LLM Integration & Agentic System Development
- Design and implement agentic AI systems with multi-step reasoning, planning, and autonomous tool selection capabilities
- Integrate LLM-based features including Q&A, summarization, recommendations, and SQL Agents into production applications
- Apply advanced prompt engineering techniques (chain-of-thought, ReAct, Plan-and-Execute) to improve relevance, accuracy, and quality of AI outputs
- Build and maintain tool-use architectures enabling agents to dynamically invoke search, SQL execution, APIs, and code generation
- Implement short-term and long-term memory systems for context persistence across agent interactions
- Design multi-agent coordination patterns including delegation, handoffs, and parallel execution workflows
- Collaborate with stakeholders on data preparation, usage patterns, and requirements for AI-powered features
Data Processing & Knowledge Engineering
- Develop pipelines to convert unstructured data (PDFs, emails, documents) into structured, queryable formats using text extraction models and NLP techniques
- Build and integrate knowledge graph representations to enhance agent reasoning and retrieval capabilities
- Write optimized SQL queries and design schemas to support dynamic query generation by SQL Agents
- Implement data chunking, normalization, and metadata enrichment strategies for AI consumption
Cloud Deployment & DevOps
- Deploy and manage agentic AI services using AWS (ECS, ECR, S3, RDS, Bedrock, Lambda, CloudFormation)
- Containerize application services and agent runtimes using Docker
- Implement and maintain CI/CD pipelines using GitHub Actions, AWS CodeBuild/CodePipeline
- Manage infrastructure as code for reproducible, scalable environments
- Monitor agent performance, latency, and cost using observability tooling
Quality, Safety & Governance
- Implement guardrails, output validation, and permission boundaries for autonomous agent actions
- Design human-in-the-loop checkpoints for high-risk or sensitive operations
- Build evaluation frameworks measuring task completion, tool efficiency, and reasoning quality
- Ensure error recovery, graceful degradation, and fallback strategies in multi-step agent flows
Required Qualifications
- Education: Bachelor's or Master's degree in Computer Science, Data Science, AI/ML, or a related field
- Experience: 35 years of professional experience in software development with at least 12 years focused on LLM/AI application development
- Python: Strong proficiency in Python for backend development, API design (FastAPI/Flask), and AI/ML integration
- SQL: Solid skills in query writing, optimization, and schema design
- LLM Frameworks: Hands-on experience with at least one agent orchestration framework (LangChain, LangGraph, CrewAI, AutoGen, or Claude Agent SDK)
- Prompt Engineering: Demonstrated ability to design effective prompts for multi-step reasoning, tool selection, and structured outputs
- Cloud (AWS): Working experience with ECS, ECR, S3, RDS, and CloudFormation
- Containers & CI/CD: Proficiency with Docker and at least one CI/CD platform (GitHub Actions, CodePipeline)
- Version Control: Strong Git practices including branching strategies and code review workflows
Preferred Qualifications
- Experience evolving RAG pipelines into agentic architectures in production environments
- Familiarity with knowledge graph databases (Neo4j, Amazon Neptune) and graph-based retrieval
- Experience with text extraction and document parsing (spaCy, Tesseract, Amazon Textract)
- Exposure to observability platforms for LLM applications (LangSmith, Arize, Weights & Biases)
- Understanding of vector databases (Pinecone, Weaviate, pgvector) and hybrid retrieval strategies
- Experience with AWS Bedrock or similar managed LLM services
- Knowledge of async programming patterns and event-driven architectures
Job Classification
Industry: IT Services & ConsultingFunctional Area / Department: Data Science & AnalyticsRole Category: Data Science & Machine LearningRole: Machine Learning EngineerEmployement Type: Full timeContact Details:
Company: CapgeminiLocation(s): Bengaluru
Keyskills: Agentic Ai LLM Python Prompt Engineering Langchain Github Aiml Devops AWS
Similar positions
Capgemini
Capgemini Engineering combines, under one brand, a unique set of strengths from across the Capgemini Group: the world leading engineering and R&D services of Altran acquired by Capgemini in 2020 - and Capgemini's digital manufacturing expertise. With broad industry knowledge and cutting-edge ...
Job Listings
We are in open beta version of website, please let us know if any issues, at: info(at)indigojobs.in