Agentic AI Engineer

Agentic AI Engineer

Experience: 47 years

Location: Bangalore / New Delhi / Gurugram

Availability: This is an urgent requirement Immediate joiners preferred

Overview

Design, build, and operate production-grade AI agents and tools using Agentic AI frameworks in Python. You will own agentic workflows end-to-end across planning, reasoning, tool calling, retrieval, evaluation, security, and observability.

Key Responsibilities

• Agent Development: Implement agentic workflows in Python using an agent framework (Semantic Kernel preferred; LangGraph, AutoGen, or CrewAI acceptable).
• Tool Orchestration: Build reliable tool and function-calling flows with planning, memory, and conversation orchestration.
• Retrieval Pipelines: Develop retrieval pipelines for RAG and hybrid search, including ingestion, chunking, embeddings, ranking, query planning, grounding, and caching.
• Cloud Deployment: Deploy agents to production on cloud platforms, integrating identity, networking, cost controls, and runtime observability.
• Monitoring & Observability: Instrument applications with tracing, metrics, and logs to ensure performance and reliability.
• Evaluation Workflows: Establish evaluation workflows using prompt and flow tests for offline, batch, and A/B scenarios.
• System Hardening: Collaborate with product, data, and security teams to harden systems using rate limits, retries, timeouts, and circuit breakers.
• Documentation & Mentorship: Maintain clear technical documentation and provide mentorship to peers on best practices and debugging.

Must-Have Qualifications

• 45 years of hands-on GenAI application experience before transitioning into agentic system work.
• Strong proficiency in Python 3.11+ (typing, asyncio, packaging, testing with pytest, profiling, CI/CD).
• Production experience with at least one agent framework (Semantic Kernel preferred ; LangGraph/AutoGen/CrewAI acceptable).
• Proven expertise in tool/function calling , schema design, argument validation, and multi-step planning.
• Experience with retrieval systems using vector stores and hybrid search, including grounding and retrieval evaluation.
• Cloud deployment experience with containers, secrets/identity management, networking, monitoring, and alerting.
• Strong skills in observability and evaluation (tracing, metrics, log aggregation, experiment design, promotion criteria).
• Solid understanding of security and safety fundamentals: P rompt-injection defenses, content policy enforcement, sandboxing, and PII handling.
• Clear and effective technical communication with strong collaborative and review practices.

Good-to-Have Skills

• Multi-agent patterns (task decomposition, coordinatorworker, human-in-the-loop).
• Deeper Azure experience, including Azure AI Search and related AI platform services.
• Evaluation experience with regression suites, red teaming, and guardrails .
• Proficiency in search/data stores (Elasticsearch, Pinecone, pgvector, Azure AI Search).
• Frontend integration for agent UIs with streaming/tool traces and secure API design.
• DevOps proficiency with Docker, Kubernetes, GitHub Actions/Azure DevOps, IaC, and secrets management.