About the job
We’re hiring an Early Access Deployment Engineer to lead technical engagements with customers who are leveraging our frontier capabilities to solve real-world use cases. You will work at the earliest—and often messiest—stage of development, when capabilities are still unclear, tooling and processes are evolving, and the path from promising technology to a valuable real-world application has yet to be defined.
Responsibilities
- Engage deeply with strategic customers during the earliest alpha stages to understand their goals, workflows, technical constraints, and highest-value opportunities.
- Translate emerging and ambiguous model capabilities into scoped use cases, working prototypes, and clear success criteria.
- Prototype rapidly with customers, Product, and Research through experiment-driven iteration.
- Design and support evaluations that reveal model behavior, solution quality, workflow impact, and failure modes.
- Evaluate and troubleshoot based feedback across product, model behavior to determine patterns and gaps
- Own early access program execution end to end, from customer onboarding and live experimentation through synthesis and launch decisions.
- Align Research, Product, Engineering, GTM, Legal, Security, Marketing, and launch teams by communicating risks, tradeoffs, and recommendations clearly.
- Codify architectures, evaluation methods, technical patterns, and program learnings into reusable playbooks that improve future deployments.
Qualifications
Minimum
- Have 4+ years of software engineering or equivalent technical experience, including meaningful customer-facing delivery and ownership of production systems.
- Have a track record of rapidly turning ambiguous ideas into working prototypes and carrying the strongest approaches through to reliable solutions. Can demonstrate examples of systems thinking.
- Be proficient in Python and/or JavaScript or TypeScript, comfortable across modern front-end and back-end development, and familiar with cloud deployment.
- Bring practical AI and LLM depth, including experience reasoning about model behavior, designing evaluations, and building production-oriented AI applications.
Preferred
No preferred qualifications listed.