Staff AI Engineer - OpenClaw

STAFF AI ENGINEER

Agentic AI & LLM Infrastructure | High-Growth (Series B, $100M+ raised)

Our client is a hyper-growth, venture-backed company on a mission to make financial services radically more accessible for underserved communities. Their flagship product is an AI-powered conversational platform used by customers every day to move money — fast, affordable, and as easy as sending a text.

Now they're building their next chapter: a new Enterprise AI squad, and they need a Staff AI Engineer to architect it.

You'll be the technical anchor behind the company's central AI orchestrator and its distributed execution agents - evolving a production conversational AI platform into a sophisticated multi-agent system capable of reasoning, planning, and automating complex workflows across critical functions like payments, lending, and fraud.

This is a foundational hire. You'll shape the architecture of a brand-new squad, define what gets built next, and set the standard for how AI is deployed across the business.

Responsibilities:

• Architect and scale the core infrastructure for a central AI orchestrator and its connected execution agents
• Lead infrastructure-first AI development - owning the full lifecycle from containerization (Docker/Kubernetes) through CI/CD, availability, security, and post-launch stability
• Build production-grade LLMOps and observability: tracing reasoning paths, tool-calling success rates, and latency bottlenecks across complex agentic workflows
• Design automated "evals-as-code" pipelines using LLM-as-a-judge, semantic similarity testing, and adversarial benchmarking
• Optimize RAG pipelines and agent loops for production - caching, prompt compression, and model routing to balance cost and performance
• Set operational best practices for AI deployment and help map out future team and infrastructure needs

Required Skills:

• 8+ years of hands-on software engineering, with a proven background in infrastructure and systems development
• 2+ years building and deploying production-grade LLM applications
• Exceptional Python and deep system architecture expertise; mastery of core LLM APIs and agentic frameworks
• Proven experience with complex agentic systems: RAG, tool-calling, vector databases, and advanced memory/state management
• High ownership and comfort in an early-stage squad - someone who can spot operational bottlenecks, propose the architecture, and ship it
• Bonus: hands-on experimentation with Open CLAW, Hermes, or other advanced open-source agent frameworks

If you thrive at the intersection of deep infrastructure, operational excellence, and agentic AI this is your mission.

Interested or know someone great? Apply here or DM me directly. All conversations are strictly confidential.