Embedded AI Deployment Engineer

Cursor; Australia; On-site; AUD 180,000 - 260,000; Full time

Job summary

SpaceX is seeking an engineer to embed with customer teams, own an outcome, and ship a production-grade SpaceXAI system that remains operational after you depart.

You’ll design and deploy production agents on Grok, wire them into the customer’s auth, data, and tools, and harden them with evals until adoption is achieved. This role demands end-to-end responsibility and practical impact in real-world use cases.

Qualifications

• 5+ years in software/ML engineering or data science.
• Proficient in Python and JavaScript/TypeScript.
• Owns a customer outcome, ships production systems.
• Experience with AI-native workflows and production failures.
• Strong reliability mindset: metrics, alerts, incident response.
• End-to-end ownership: frontend, backend, infra, and prompt iteration.
• Able to discuss with engineers and leadership (VP level).

Responsibilities

• Lead discovery with the customer, map codebases and workflows, define clear success metrics.
• Design and ship production agents and AI applications on Grok in live business processes.
• Get a first version live in days and harden it with rollout and iteration.
• Own production quality: tracing, evals, debugging failures, latency and cost tradeoffs.
• Build the systems around the model (tools, servers, retrieval, rules) and integrate with auth/data/workflow.
• Measure outcomes (revenue, cost, hours saved, defect rate) rather than seat adoption.
• Collaborate with Staff+, platform, and domain leaders, then share learnings as reusable patterns.

Skills

5+ years experience

Python

JavaScript/TypeScript

Production code

End-to-end system design

Tools

Grok

CI/CD

Eval harnesses

MCP servers

Retrieval systems

Job description

SpaceX is seeking an engineer to embed with customer teams, own an outcome, and ship a production-grade SpaceXAI system that remains operational after you depart.

You’ll design and deploy production agents on Grok, wire them into the customer’s auth, data, and tools, and harden them with evals until adoption is achieved. This role demands end-to-end responsibility and practical impact in real-world use cases.