AI Engineer

POSITION SUMMARY:

This is a builder role end-to-end: design and ship agentic systems from tool interface through deployment, observability, and iteration working closely with product and customers. This is not a research role, and it is not prompt engineering; the team builds production systems that use AI to solve real problems at scale.

RESPONSIBILITIES:

Build & Ship

• Design and build MCP servers that expose data and analytics as discoverable, reliable tools for AI agents, with proper auth, scoping, and access controls

• Architect and ship agentic workflows: multi-step reasoning, tool use, orchestration patterns, and human-in-the-loop where needed

• Develop AI connectors integrating the company's intelligence with external agents, clients, and downstream systems

• Own the full lifecycle API/tool design, deployment, monitoring, production hardening

Reliability & Iteration

• Use evals to validate agent behavior before shipping, catch regressions, and debug production divergence

• Build observability and tracing to make agent behavior inspectable and auditable

• Tune for latency, cost, and reliability as models and data drift

Execution & Collaboration

• Partner with Product Builders, design, and customers to ship working software (not prototypes)

• Build internal SDKs, reusable patterns, and shared context that raise the floor for the whole team

• Stay close to the fast-moving MCP/agent ecosystem and bring back what's relevant

QUALIFICATIONS:

• 3 7+ years of software engineering experience, with production systems shipped end-to-end

• Strong Python backend fundamentals; comfortable owning services from design through deployment (fullstack a plus)

• Hands-on experience building and operating LLM-powered agents in production with concrete stories of what broke, how you fixed it, and what you'd do differently

• Practical familiarity with agentic patterns: tool use, structured outputs, prompt chaining, multi-agent coordination, and knowing when a deterministic workflow is the right call

• Experience designing/building MCP servers or equivalent tool-use / AI connector integrations

• Have used evals to validate and debug agent behavior

• Comfortable with cloud deployment (GCP/AWS), containerized services, and async Python

• Strong product instinct thinks about what users actually need and pushes back when a spec doesn't add up

BENEFITS SUMMARY: Individual compensation is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base hourly rate or annual salary only, unless otherwise stated. In addition to base compensation, full-time roles are eligible for Medical, Dental, Vision, Commuter and 401K benefits with company matching.

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