JOBSEARCHER

Full-Stack Product Engineer (AI-Native)

ARCHIVED

We can't find an active application page for this role right now. It may reopen or be listed elsewhere. Use Next Steps to search for an active apply link and similar live jobs.

Job Title: Full-Stack Product Engineer (AI-Native)Location: Hybrid (must be able to come to office in Encino, CA 2-3 days per week)Type: Full-time (40-hour workweek)We’re hiring a product-minded full-stack engineer who can take a feature from a design/idea all the way to a shipped, monitored, iterated product. You’ll work across frontend + backend, make pragmatic product and technical tradeoffs, and use modern AI coding assistants (Claude Code/GitHub Copilot CLI/similar) to move faster — while staying fully accountable for correctness, security, and maintainability.This is not a “just implement tickets” role. You’ll own outcomes.What you’ll do:Own features end-to-endClarify the problem, ask the right questions, and define success metricsPropose solution options with tradeoffs (scope/speed/quality)Implement, ship, monitor, and iterate based on real usagePartner tightly with Design/ProductTurn designs into polished UI/UX; handle edge cases, loading/error states, and responsive behaviorTranslate ambiguous requirements into a clear plan and incremental milestonesFull-stack executionBuild and maintain frontend + backend components: UI, APIs, data models, workflows, integrationsDesign clean, versionable API contracts (pagination, errors, auth, backwards compatibility)Work effectively in an event-driven/CQRS architectureRespect boundaries, choose appropriate patterns, and keep systems evolvableHandle idempotency, retries, and failure modes cleanlyAI-assisted engineering (must be real, not buzzwords)Use Claude Code / Copilot CLI / similar tools to speed up implementation, debugging, and codebase navigationStay in control: plan first, review diffs carefully, write tests, and verify behavior locallyLocal-first engineeringRun the stack locally end-to-endSeed data, reproduce issues deterministically, and debug effectivelyImprove developer experience (scripts, docs, environment reliability)Quality bar ownershipWrite the right tests (unit/integration/e2e as appropriate)Add logging/telemetry that makes production understandablePrevent regressions and keep performance/reliability strongCode review excellenceReview PRs for correctness, security, performance, readability, and long-term maintainabilityGive clear feedback and raise the bar without slowing the team downPragmatic security mindsetApply best practices for secrets handling, authn/authz, input validation, dependency hygiene, rate limiting, and secure defaultsWhat we’re looking for (must-haves):Proven end-to-end feature ownership in a real product (ship → monitor → iterate)Strong product intuition: understands workflows, edge cases, success metrics, and tradeoffs; can make sensible product decisions when requirements are ambiguousFull-stack capability: comfortable building both UI and backend services; experience designing APIs and evolving data models safelySolid system design fundamentals: can reason about boundaries, modularity, maintainability, and operational impactReal experience with AI coding assistants in daily development: hands-on with Claude Code or GitHub Copilot CLI or equivalent (Cursor, Codex, etc.); can explain your workflow (when you trust AI output, how you verify, and how you avoid regressions/security issues)Ability to run and debug complex systems locally (not “works on my machine”)Strong communication: breaks work into slices, documents decisions briefly, surfaces risk early, and keeps stakeholders updatedMust be available to come into headquarters (Encino, CA) at least once per month! Nice-to-haves:Angular experience (or deep experience in another modern frontend framework + willingness to ramp fast).NET / C# experience (or strong backend experience + willingness to ramp fast)Hands-on experience with event-driven systems / CQRS patternsExperience working closely with QA in a structured handoff and feedback loopFamiliarity with observability tooling (structured logs, metrics, tracing)Comfort experimenting quickly (“vibe coding”) paired with discipline (tests, reviews, safe rollouts)Compensation and Benefits:$160K - $220K base salaryBonus: Up to 10% of base (determined annually in December)Healthcare: Medical, Dental, and Vision plan optionsRetirement: 401(k) with up to 4% company matchPerks:High-impact role in a rapidly scaling AI companyCollaborative, product-focused team environmentUnlimited snacks, coffee, and more (if based in Los Angeles, CA)Weekly team happy hours (if based in Los Angeles, CA)Business trips and team-building eventsReady to shape the future of AI-powered legaltech?APPLY NOW!