Python Developer

Role- Responsibilities

• Implement agentic workflows in Python using an agent framework. Semantic Kernel is

preferred. Experience with LangGraph, AutoGen, CrewAI, or equivalent is valuable.

• Build reliable tool and function calling flows with planning, memory, and conversation

orchestration.

• Develop retrieval pipelines for RAG and hybrid search including ingestion, chunking,

embeddings, ranking, query planning, grounding, and caching.

• Ship agents to production on cloud platforms. Integrate identity, networking, cost controls,

and runtime observability.

• Instrument applications with tracing, metrics, and logs.

• Establish evaluation workflows using prompt and flow tests for offline, batch, and A/B

scenarios.

• Collaborate with product, data, and security to harden systems using rate limits, retries,

timeouts, and circuit breakers. Provide documentation and mentorship.

Must have

• 4 to 5 years hands on GenAI application experience before moving to agentic work.

• Strong Python 3.11 plus skills including typing, asyncio, packaging, testing with pytest,

profiling, and CI/CD.

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

LangGraph, AutoGen, or CrewAI acceptable.

• Expertise in tool and function calling, schema design, argument validation, and multi-step

planning.

• Retrieval systems experience with vector stores and hybrid search. Familiarity with

grounding strategies and retrieval evaluation.

• Cloud deployment experience with containers, secrets and identity, networking,

monitoring, and alerting.

• Observability and evaluation proficiency including tracing, metrics, log aggregation,

experiment design, and promotion criteria.

• Security and safety fundamentals including prompt injection defenses, content policy

enforcement, tool sandboxing, and PII handling.

• Clear technical communication and collaborative code reviews.

Good to have

• Multi agent patterns such as task decomposition, coordinator worker, and human in the

loop.

• Deeper Azure experience including Azure AI Search and related AI platform services.

• Evaluation depth with regression suites, red teaming, and data driven guardrails.

• Search and data store depth with Elasticsearch, Pinecone, pgvector, or Azure AI Search.

• Frontend integration for agent UIs with streaming and tool traces. Secure API design for

tools and connectors.

• DevOps skills with Docker, Kubernetes, GitHub Actions or Azure DevOps, infrastructure as

code, and secrets management.