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Senior / Lead AI Production Engineer (SpaceXAI)

Cursor· SpaceXSI / SpaceXAI
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RemoteFull-timePosted 3mo ago

About the role

Engineer embedded with customer teams to design, ship, and operate production-grade SpaceXAI systems end-to-end, from discovery through post-launch support, with a strong emphasis on real-world outcomes and reusable patterns for SpaceXAI products.

Responsibilities

  • Lead discovery with the customer: orient in their codebases and workflows, find the real bottleneck and the use case worth building, and define clear success metrics
  • Design and ship production agents, AI applications, and coding-agent workflows on Grok and our models, on live business processes and inside the customer’s engineering org
  • Get a first version live in days, then harden it over weeks with rollout, monitoring, and iteration from real usage
  • Own production quality: tracing, evals, debugging model or delivery failures, and latency and cost tradeoffs
  • Build the systems around the model (tools, MCP servers, retrieval, rules, skills, CI gates, and evals) and integrate them into the customer’s auth, data, workflow, and delivery systems; decide when prompting, architecture, data, process, or a model change is the right lever
  • Measure the outcome that matters (revenue, cost, hours saved, error rate, cycle time, escaped defects), not seat adoption
  • Work directly with Staff+, platform, and domain leaders, going deep in their systems while communicating clearly about tradeoffs and results
  • Leave the customer team able to run what you built, and turn what you learn into reusable patterns and improvements to SpaceXAI products

Qualifications

  • 5+ years of experience in software engineering, machine learning engineering, or data science
  • Proficient in production code (Python, JavaScript/TypeScript; other languages welcome)
  • Experience owning customer or operator outcomes and turning fuzzy problems into scoped, shipped systems
  • Built and owned AI-native workflows or agents in production; debugged real production failures (model, tool, data, pipeline, or delivery path)
  • Handled production reliability: metrics, alerts, safe rollouts, incident response
  • Experience building end-to-end systems: frontend, backend, infra, and prompt iteration
  • Thrives in ambiguity and can work without complete specs
  • Ability to communicate with engineers and with executives (VP level)

Skills

Required:Customer discovery and requirements shapingProduction-grade software engineeringPythonAI model integration and evals
Nice to have:JavaScript/TypeScriptMCP servers / retrieval / rules / skills

Benefits

  • Not specified in the description
Last updated Oct 15, 2026. Interested? Apply on the company site.
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