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agent-orchestration jobs in San Diego

$230,000 – $311,000 · Posted 1 day ago

Lead product strategy and roadmap for Intuit's next-generation Agentic AI Platform, designing core execution frameworks, agent libraries, and SDKs that enable complex reasoning and autonomous task execution across TurboTax, QuickBooks, Mailchimp, and Credit Karma. Define extensible platform architecture, drive multi-step planning and orchestration capabilities, and ensure agent observability and trust at scale. Partner closely with engineering and architects to standardize agent development, deployment, and management while mentoring other product managers on technical fluency and platform thinking.

San DiegoLast seen today
$140,000 – $190,000 · Posted 2 days ago

Founding Product Engineer to build a greenfield physical AI product at Netradyne, working across full-stack infrastructure, product UX, and agentic AI features. You'll design multi-tenant cloud and edge systems on AWS with real-time dashboards, compliance analytics, and AI-powered agent orchestration for safety operations. Expected to own end-to-end problems—from device to cloud to customer—with 7+ years of software engineering across backend (Go, Python, Java), cloud infrastructure (containers, CI/CD, distributed systems), and modern frontend (TypeScript/JavaScript). Direct customer collaboration and rapid iteration in the field required; fluency with AI-assisted development tools (Claude, Cursor) expected.

San DiegoLast seen today
Posted 9 days ago

Build the foundational agentic AI layer for a materials-science platform, including multi-model provider abstraction, agent orchestration with stateful checkpoints, retrieval systems, prompt versioning, and comprehensive tracing and evaluation frameworks. You'll design agents that plan and reason over tool calls in production, implement human-in-the-loop safety gates, and ensure all LLM behavior remains auditable and cost-tracked across customers' secure environments. The role demands deep production experience with agentic and LLM systems: async Python, structured outputs, memory and context management, multi-step workflow orchestration, and evaluation harnesses that catch regressions before deployment.

San DiegoLast seen 7 days ago