Agentic AI Engineer
1 week ago
Agentic AI EngineerExperience: 4–7 yearsLocation: Bangalore / New Delhi / GurugramAvailability: This is an urgent requirement – Immediate joiners preferredOverviewDesign, 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- 4–5 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: Prompt-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, coordinator–worker, 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.
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