Agentic AI Engineer

5 days ago


New Delhi, India Lara Tech Consulting Full time

Agentic AI EngineerExperience:4–7 years Location:Bangalore / New Delhi / Gurugram Availability:This is an urgent requirement – Immediate joiners preferredOverview 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 4–5 years of hands-onGenAI application experiencebefore transitioning into agentic system work. Strong proficiency inPython 3.11+(typing, asyncio, packaging, testing with pytest, profiling, CI/CD). Production experience with at least oneagent framework(Semantic Kernel preferred; LangGraph/AutoGen/CrewAI acceptable). Proven expertise intool/function calling, schema design, argument validation, and multi-step planning. Experience withretrieval systemsusing vector stores and hybrid search, including grounding and retrieval evaluation. Cloud deployment experiencewith containers, secrets/identity management, networking, monitoring, and alerting. Strong skills inobservability and evaluation(tracing, metrics, log aggregation, experiment design, promotion criteria). Solid understanding ofsecurity and safety fundamentals: Prompt-injection defenses, content policy enforcement, sandboxing, and PII handling. Clear and effectivetechnical communicationwith strong collaborative and review practices.Good-to-Have Skills Multi-agent patterns (task decomposition, coordinator–worker, human-in-the-loop). Deeper Azure experience, includingAzure AI Searchand related AI platform services. Evaluation experience withregression suites, red teaming, and guardrails. Proficiency in search/data stores (Elasticsearch, Pinecone, pgvector, Azure AI Search). Frontend integration foragent UIswith streaming/tool traces and secure API design. DevOps proficiencywith Docker, Kubernetes, GitHub Actions/Azure DevOps, IaC, and secrets management.


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