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AI Agent Engineer
AI Agent EngineerRecro • Bengaluru, Karnataka, India
AI Agent Engineer

AI Agent Engineer

Recro • Bengaluru, Karnataka, India
30+ days ago
Job description

⭐ Agentic AI Engineer ⭐ Location : India (Hybrid / On-site depending on project)

About the Role

We are hiring a highly skilled Agentic AI Engineer, one of the world’s leading professional services organisations.

You will design, build, evaluate, and productionize Agentic AI systems using advanced frameworks and modern AI engineering practices.

This is a high-impact engineering role designed for professionals who have built end-to-end GenAI applications and are now moving deeper into agentic architectures .

Key Responsibilities

Architect, develop, and deploy production-grade AI Agents using Semantic Kernel , LangGraph , AutoGen , CrewAI , or equivalent frameworks.

Build advanced tool / function calling pipelines , memory components, planning modules, and orchestrated multi-step agent workflows.

Design and optimize RAG pipelines including ingestion, chunking, embeddings, hybrid search, grounding, ranking, and evaluation.

Deploy agents on cloud (Azure / GCP / AWS) with strong focus on identity, networking, logging, cost optimization, and monitoring.

Implement strong observability including tracing, metrics, logs , experiment tracking, and A / B evaluation.

Establish automated evaluation + regression suites for agent reliability, safety, and performance.

Collaborate closely with product, data, and security teams to ensure agents comply with safety, governance, content policies, and PII guidelines .

Provide mentorship, documentation, and best practices for scalable agentic development.

Must-Have Skills

4–6 years of hands-on GenAI application development , followed by experience building agentic systems.

Strong Python 3.11+ skills : asyncio, typing, packaging, profiling, CI / CD, pytest.

Production experience with at least one agent framework ( Semantic Kernel preferred ).

Expertise in tool calling , schema design, argument validation, planning modules.

Deep knowledge of vector databases , hybrid RAG, retrieval optimization, evaluation metrics.

Cloud deployment experience with Docker, containers, secrets, monitoring, observability .

Strong understanding of prompt security , PII governance, sandboxing, and safe tool execution.

Excellent communication + collaborative engineering mindset.

Great to Have

Experience with multi-agent patterns : task decomposition, coordinator-worker, HITL loops.

Azure Search, Pinecone, Elasticsearch, pgvector.

Frontend integration for AI agent UIs with streaming events + tool traces.

DevOps pipeline experience (GitHub Actions, Azure DevOps, Kubernetes, IaC).

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