Senior AI Engineer, Agentic Systems
RemoteUnited States
Job Summary
Design multi-agent architectures with robust state management, memory, and routing using frameworks like LangGraph, AutoGen, or CrewAI. Integrate enterprise tools via function calling and webhooks, implementing RAG patterns with vector stores and deterministic fallbacks to ensure predictable latency and cost. Define SLIs/SLOs for agent runs, build evaluation harnesses for grounding and safety, and productionize systems with CI/CD, feature flags, and canary strategies. Enforce content policies with policy-as-code, implement role/tenant isolation, and collaborate with security teams to align with ISO 27001, SOC 2, and HIPAA contexts. Work directly with enterprise clients to translate business processes into agentic designs and present proofs-of-value.
Required Qualifications
- 5–8+ years in software/platform engineering with recent production LLM applications (not just prototypes)
- Hands-on expertise with agentic frameworks (one or more of: LangGraph/LangChain Agents, AutoGen, CrewAI, LlamaIndex Agents, Semantic Kernel, Haystack Agents) and tool/function-calling patterns
- Strong RAG engineering across vector DBs, chunking/embedding strategies, metadata/search ranking, and grounding techniques
- Proven track record building observable, cost-aware, and secure LLM systems (tracing, evals, guardrails, secrets/IAM, PII handling)
- Solid software engineering fundamentals: Python/TypeScript, async patterns, APIs, testing, CI/CD, containerization
- Clear communicator who can interface with clients and write crisp technical docs
Desired Qualifications
- Azure-first experience (Azure OpenAI, Azure AI Studio, Azure Functions/Container Apps/AKS, Private Link/VNet, Key Vault, Entra ID)
- Cross-cloud exposure (AWS/GCP) and hybrid integrations; experience with enterprise connectors (SharePoint/OneDrive, ServiceNow, Salesforce)
- Experience with structured output, constrained decoding, JSON Schemas, and program-of-thought planning
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