Applied AI Senior Engineer

Must-Have Requirements

Requirement Details

Backend/Systems Experience

3+ years building production backend or distributed systems (pre-AI experience required)

Production AI Systems

Has shipped AI/LLM features serving real users at scale — not just prototypes or demos

Agentic Systems

Has built AI agents, skills, tools, or MCP (Model Context Protocol) integrations

Python

Proficient for backend development

Secondary Language

Working knowledge of Go, TypeScript, or Rust

Cloud Infrastructure

Deep experience with AWS/GCP/Azure — cost optimization, compute decisions, not just deployment

Container & Orchestration

Hands-on with Docker and Kubernetes — can build, deploy, debug, and scale services themselves

LLM Integration

Understands token economics, context limits, rate limiting, structured outputs, API failure modes

LLM Evaluation

Understands how to evaluate LLM outputs and the inherent challenges (non-determinism, quality measurement, regression detection)

Hands-On Engineer

Not just an architect — writes code, debugs production issues, deploys their own work

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Preferred / Differentiators

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Screening Questions for Candidates

1. "Describe a production AI agent or skill system you built. What broke and how did you fix it?"

2. "Have you built MCP servers/integrations or custom tool-use systems for LLMs?"

3. "How do you evaluate whether an LLM-based feature is working well? What makes this hard?"

4. "Walk me through how you'd deploy and scale an AI service on Kubernetes."

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Not a Fit If

Location : Sunnyvale, CA/Austin, TX

Salary Range: $70,000-$150,000 a year

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