Description

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

This role is hybrid.

Responsibilities

• Architect 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 platforms (Azure/GCP/AWS) focusing on identity, networking, logging, cost optimization, and monitoring.
• Establish automated evaluation and regression suites for agent reliability, safety, and performance.

Required Skills

• 5+ years of hands-on GenAI application development, with specific experience building agentic systems.
• Strong Python 3.11+ skills: asyncio, typing, packaging, profiling, CI/CD, pytest.
• Production experience with at least one agent framework, with Semantic Kernel preferred.
• Expertise in tool calling, schema design, argument validation, and planning modules.
• Deep knowledge of vector databases, hybrid RAG, retrieval optimization, and evaluation metrics.
• Cloud deployment experience with Docker, containers, secrets, monitoring, and observability.
• Strong understanding of prompt security, PII governance, sandboxing, and safe tool execution.
• Experience with CI/CD pipelines and familiarity with Azure, GCP, or AWS environments.

Preferred Skills

• Experience with multi-agent orchestration patterns.
• Background in LLM fine-tuning or model optimization.

Key Skills

Education

Any Graduate