Artificial Intelligence Engineer
4 hours ago
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.
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