Senior AI Data Engineer

Position Details:-

Experience: 6-9 Years

Work Location: Gurugram (Hybrid)

Mode: Full Time Permanent

Job Description:

We are hiring mid-to-senior level Agentic / Generative AI Engineers (6–9 years’ experience) to design and deliver production-grade LLM-powered and agentic systems. This role is ideal for engineers with a strong Data Engineering / Data Science foundation who have transitioned into hands-on GenAI delivery—building real-world solutions such as RAG based assistants, document intelligence platforms, and agent-driven workflows. You will collaborate across data, platform, and business teams to build secure, scalable, and measurable AI applications for enterprise use cases.

Key Responsibilities :

 Design and develop LLM-powered applications using agentic patterns (single/multi agent) for business use cases

 Build and optimise end-to-end RAG pipelines (ingestion, embeddings, retrieval, orchestration, response synthesis)

 Implement prompt engineering and orchestration techniques (prompt chaining, tool/function calling, structured outputs)

 Develop production-grade APIs and services (FastAPI/Flask/Streamlit) for GenAI applications

 Integrate LLM solutions with enterprise systems, data platforms, and workflows  Apply guardrails and evaluation frameworks to improve response quality, reduce hallucinations, and ensure responsible AI usage

 Collaborate with Data Engineering and MLOps teams for data pipelines, deployment, monitoring, and scaling

 Contribute to reusable components, documentation, and engineering best practices

Experience & Core Requirements (Must-Have)

Overall Experience
 6–9 years total experience

 1–3+ years in hands-on GenAI / LLM application development (production use cases)

LLM / GenAI & Agentic Engineering

 Strong hands-on experience with:

o LLMs (Claude, OpenAI, etc.)

o RAG pipelines and retrieval optimisation

o GPT + Agentic AI implementation experience

 Experience with:
o LangChain, LangGraph, or similar frameworks
o Agent orchestration and tool-calling architectures

 Deep understanding of:
LLM limitations, evaluation, and optimisation strategies

Pay: ₹2,000,000.00 - ₹3,000,000.00 per year

Benefits:

• Health insurance
• Life insurance
• Paid time off
• Provident Fund

Work Location: In person