Agentic AI Developer - Orchestration
Major telecommunications equipment company · Sunnyvale, CA
- Location
- Sunnyvale, CA · Onsite
- Salary band
- Band not stated
- Type
- Contract
- Level
- Senior
- Work authorization
- Not stated
Stack
Agentic AI · Agent Orchestration Frameworks · LangGraph · Semantic Kernel · AutoGen · CrewAI · MCP · RAG · REST · gRPC · Vertex AI · GKE · Cloud Run · CI/CD · Infrastructure as Code · Kafka · Pub/Sub · Python · GitLab · Jira
About the role
Title: Agentic AI Developer - Orchestration Duration: Long term contract Location: Sunnyvale, CA Interview: Video interview Note: Onsite Job Description: Key Responsibilities- - Build reusable agent infrastructure, orchestration capabilities, interfaces, connectors, context [contact hidden], evaluation, and observability for [contact hidden] AI-Native Core products. Skill Requirements- - Design reusable agent runtimes using LangGraph, Semantic Kernel, AutoGen, CrewAI, and workflow engines. - Develop orchestration frameworks supporting stateful, multi-agent, and event-driven execution patterns. - Create capability registries, tool catalogs, SDKs, and reusable service interfaces. - Build enterprise MCP ecosystems, including servers, clients, gateways, and reusable integrations. - Implement shared context [contact hidden], memory management, session persistence, and conversation lifecycle controls. - Engineer common RAG [contact hidden], including ingestion, indexing, embeddings, retrieval, reranking, and grounding. - Develop REST/gRPC APIs for orchestration, capability discovery, workflow execution, and agent management. - Build reusable connectors for GitLab, Jira, databases, cloud [contact hidden], APIs, and enterprise repositories. - Integrate Vertex AI model hosting, routing, quota management, streaming, and cost optimization. - Implement workflow resilience using retries, compensations, fallback strategies, and timeout controls. - Build evaluation frameworks covering task success, safety, latency, reliability, and regression testing. - Implement distributed execution using Pub/Sub, Kafka, queues, schedulers, and asynchronous workflows. - Provide end-to-end observability for models, prompts, workflows, tools, and platform [contact hidden]. - Deploy platform [contact hidden] on GKE and Cloud Run using CI/CD, Infrastructure as Code, and automated release gates. - Deliver reusable reference implementations and onboarding assets consumable across [contact hidden] product teams. Must-Have Skills- - Agentic AI - Agent Orchestration Frameworks
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