FREE ACCESS
5,000–10,000 jobs/day
See all jobs on JobTailor
Search thousands of fresh jobs every day.
Discover
- Fresh listings
- Fast filters
- No subscription required
Create a free account and start exploring right away.
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in AI/ML engineering, particularly in building and operating LLM-powered systems, while making critical architectural decisions that impact high-stakes environments. Proven ability to mentor teams, enforce engineering standards, and drive technical roadmaps in a fast-paced, ambiguous setting.
Highest-signal resume keywords
AI/ML EngineeringArchitectural Decision-MakingBuild Vs. Buy AnalysisEngineering Standards EnforcementTeam Mentorship
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Backend EngineeringFull-Stack EngineeringProduction Systems ManagementDatabase ReasoningCI/CD ImplementationTooling and Automation DevelopmentReliability EngineeringMonitoring and ObservabilityPerformance OptimizationTesting Frameworks
Soft Skills
JudgmentLeadershipCommunicationProblem-SolvingAdaptability
Tools & Technologies
AI InfrastructureTest InfrastructureDeployment ToolsAutomation ToolsMonitoring Tools
Industry Keywords
High Traffic SystemsHigh Stakes SystemsProduction IncidentsSystem ReliabilitySoftware Engineering Best Practices
Tech Stack
Tools & technologiesGo
About the role
Key responsibilities & impact- Own the technical quality bar. Define what good looks like across the codebase — architecture, testing, observability, security, performance — and make it stick through design review, code review, and your own work.
- Make the architectural calls. Own the decisions that are expensive to reverse: service boundaries, data models, the shape of our AI infrastructure, how systems fail and recover. Write them down so the team knows why.
- Own build vs. buy. Decide what's core and what's a vendor. Evaluate honestly, commit clearly, and revisit when the facts change.
- Build the engineering harness. Own the tooling and automation that let people ship in parallel and reliably — CI, test infrastructure, environments, safe deploys, and AI-assisted development workflows. Push that leverage beyond the engineering team, so non-engineers can ship real changes with the system catching the mistakes.
- Lay the foundation for mission-critical systems. Our platform can't be down or quietly wrong. Build the reliability, monitoring, and safety properties that let us grow by orders of magnitude.
- Go deep where it's hardest. Take on the problems no one else can — the gnarly production incident, the system that has to be redesigned while it's running, the AI subsystem whose behavior nobody can currently explain.
- Raise the team. Mentor engineers, sharpen designs, and make everyone around you better. Multiply the team's output rather than just adding your own.
- Shape the technical roadmap with the founders. Bring a clear point of view on sequencing, risk, and where the technology is heading — for both classical systems and AI.
Requirements
What you’ll need- Staff-level experience as a backend or full-stack engineer, with a track record of owning systems that mattered — high traffic, high stakes, or both.
- Real depth in AI/ML engineering. You've built and operated LLM-powered or ML systems in production and can reason about their failure modes, evaluation, cost, and latency as fluently as you reason about a database.
- You've made architectural decisions at scale and lived with the consequences. You can talk concretely about a call you got right and one you got wrong.
- Strong judgment on build vs. buy, on when to invest in infrastructure versus ship the simple thing, and on how much rigor a given system deserves.
- You've set and enforced engineering standards on a team, in a way that made people faster rather than slower.
- You're passionate about being on the cutting edge of software engineering. Best practices are changing fast right now, and you're the person who tracks what's actually working and brings it to the team.
- You've led a team and been its bar raiser, whether or not you carried the manager title.
- You're hands-on. You still write and review code, and you'd be unhappy if you couldn't.
- You're comfortable with ambiguity. The playbook doesn't exist yet, and you're excited to write it.
Benefits
Comp & perks- Meaningful early equity
- Competitive compensation