AI Engineer - LangGraph/LangChain

Job Title : AI Engineer

Employment Type : Full-Time (Contract - 6 Months)

Working Mode : Work From Office (WFO)

Roles & Responsibilities :

- Design, develop, and deploy agentic AI solutions using LangGraph and LangChain to automate complex business processes.

- Build and manage multi-step AI workflows involving tool usage, memory management, routing, and guardrails.

- Implement and operationalize Large Language Model (LLM) integrations using AWS Bedrock, OpenAI, or Azure AI platforms.

- Develop prompt engineering strategies, orchestration frameworks, evaluation mechanisms, and cost/performance optimization techniques.

- Architect and implement multi-agent systems using planner, executor, and critic patterns with task decomposition and reflection capabilities.

- Design and deploy production-grade Retrieval-Augmented Generation (RAG) pipelines, including chunking, embeddings, vector databases, retrieval tuning, and citation generation.

- Develop scalable backend services using Python and FastAPI with clean architecture and modular design principles.

- Ensure application reliability through automated testing, code quality checks, CI/CD pipelines, and performance monitoring.

- Collaborate with cross-functional teams to build AI-driven products and solutions.

- Contribute to AI governance, security, and responsible AI implementation practices.

Qualifications & Skills :

- 6- 10 years of experience in AI/ML Engineering, Software Development, or related fields.

- Strong hands-on experience with LangGraph, LangChain, and Agentic AI architectures.

- Experience integrating and deploying LLMs using AWS Bedrock, OpenAI, Azure OpenAI, or similar platforms.

- Expertise in designing multi-agent architectures with planning, execution, reflection, fallback mechanisms, and human-in-the-loop workflows.

- Strong experience building and optimizing RAG pipelines.

- Proficiency in Python (3.10+) with FastAPI or similar backend frameworks.

- Strong understanding of software engineering best practices, including type hints, packaging, modular design, and code maintainability.

- Experience with testing frameworks such as Pytest, mocking, contract testing, and CI/CD quality gates.

- Excellent problem-solving, analytical, and communication skills.

- Ability to work effectively in a fast-paced, collaborative environment.

Nice to Have :

- Experience building data pipelines using AWS services such as S3, Glue, Lambda, Step Functions, Kinesis, Redshift, and Athena.

- Strong knowledge of PostgreSQL/RDS, including query optimization, transaction management, migrations, and connection pooling.

- Hands-on experience with asynchronous programming using aiohttp, httpx, and asyncio.

- Knowledge of concurrency patterns, timeout handling, retries, and performance optimization techniques.

- Experience with Docker, containerization, and deployment best practices.

- Familiarity with ECS, EKS, Infrastructure as Code (IaC), and CI/CD pipelines.

- Understanding of AI Governance, Data Governance, Responsible AI, and compliance frameworks.

- Exposure to cloud-native AI deployments and enterprise-scale AI solutions.