Skills

Python Generative AI LLMs RAG LangGraph LangChain FastAPI Flask Vector Databases Milvus PGVector Azure AI Foundry Docker Kubernetes CI/CD SQL

Full job details

• Design and deploy agentic generative AI solutions leveraging LLMs, RAG pipelines, context engineering, and REST APIs.

• Architect and build multi-agent automation systems using frameworks such as LangGraph or similar orchestration platforms

• Implement LLM governance architecture including prompt drift detection, auditability, and safety policies to ensure regulatory compliance.

• Develop and integrate vector database solutions for semantic search and retrieval-augmented generation.

• Collaborate cross-functionally with AI architects, product managers, and compliance teams to accelerate AI adoption across business units.

• Develop APIs using FastAPI/Flask and build interactive demos for stakeholder showcases.

• Contribute to MLOps practices including CI/CD pipelines, model monitoring, and deployment automation.

• Conduct research experiments to enhance model performance, reliability, and fairness.

• Build and maintain ML models for domain-specific tasks such as NLP, computer vision, and predictive analytics.

• Programming: Proficiency in Python; working knowledge of SQL and Java.

• GenAI & LLMs: Deep expertise in LLMs, RAG, prompt engineering, fine-tuning, and model governance.

• Frameworks: LangChain,

• APIs & Backend: FastAPI, Flask, REST API design.

• Databases: Vector databases (Milvus, PGVector), PostGRESQL.

• Cloud & MLOps: Azure AI Foundry; Docker, Kubernetes, CI/CD pipelines.

• Visualization & UI: Streamlit, basic UI/UX design principles.

Senior IT Specialist- AI Engineer (ID- 1244)

About the role