Full Stack Product Engineer (AI-Native)

Full Stack Product Engineer (AI-Native)

Location : Austin, TX preferred (hybrid); open to remote for the right candidate Type : Full time Reports to : VP of Engineering Compensation range : $105,000 to $130,000 base salary, plus benefits and any applicable equity or bonus compensationAbout Living Security

Living Security is a B2B SaaS company in human risk management — we help large enterprises understand and reduce the human side of security risk. Our customers are major enterprise security teams, and our platform increasingly runs on AI: AI-generated training content, risk scoring, and AI-native product capabilities are core to where we're headed, not bolt-ons. We're a small engineering team with an unusually high output-per-engineer model, and we're hiring builders who want that leverage.

About the Role

We are hiring a product engineer who ships outcomes, not tickets.

This is a full stack, high autonomy role for someone who develops almost entirely through AI tools — Claude Code or similar — but who can actually drive the AI because they genuinely understand how web applications work. You know the full architecture of a modern webapp: frontend, backend, APIs, databases, auth, background jobs, deployment. You know the common failure modes, the framework tradeoffs, and the problems that show up in real production systems. That understanding is what lets you direct AI aggressively instead of just accepting what it produces.

You don't need a decade of experience. You need to be a true generalist who has built complete webapps end to end, understands why they're structured the way they are, and can take an ambiguous business problem and turn it into working, shipped software without someone writing you a spec first.

The work in front of us is concrete: LLM-powered product features, integrations into the Microsoft enterprise ecosystem (Entra ID, Outlook add-ins, Teams apps), real-time reporting and dashboards, and the enterprise platform capabilities — identity, permissions, data pipelines — that large security organizations depend on.

How We Work

AI tools do most of the typing here. Your value is in the judgment layer: knowing what to build, how to structure it, when the AI's output is wrong, and what "done" actually means for the customer. If you've used AI coding tools as your primary workflow — not as autocomplete, but as the way you plan, build, test, and debug — this will feel natural. If you've mostly worked from detailed tickets inside one slice of a large system, it won't.

We run a continuous-flow model, not sprints: work is scoped into roughly one-week shippable deliverables, milestones carry the multi-week arcs, and there's minimal ceremony between you and production. Success here is measured in shipped customer outcomes, not story points or activity.

One thing to be clear-eyed about: this is a startup with hard enterprise commitments and real deadlines, and the pace reflects that. We move with genuine urgency, the team is small enough that there's no one to hand things off to, and when something matters it gets finished — not parked until the next planning cycle. People here go hard because they're building something they care about. If you're looking for a season of your career to do the most intense, highest-leverage work you've done, this is that. If you're looking for a comfortable cruising altitude, it isn't.

What You'll Do

• Own features from ambiguous problem statement through production, end to end.
• Build LLM-powered product features — generation, agents, scoring, automation — where they create clear customer value, and own their quality the same way you'd own any other code path.
• Build integrations into the enterprise ecosystems our customers live in, especially Microsoft: Entra ID, Outlook add-ins, Teams apps, and the APIs and sync jobs behind them.
• Build across the full stack: frontend, backend, APIs, databases, integrations, background jobs, and cloud infrastructure.
• Use Claude Code (or similar) as your core development workflow: planning, implementation, refactoring, testing, debugging, and documentation.
• Make practical product and architecture decisions without heavy oversight, and explain your reasoning.
• Validate AI-generated code rigorously and take full responsibility for quality, security, and maintainability.
• Ship quickly, learn from real usage, and iterate.

What We're Looking For

• Solid full stack experience building and shipping complete web applications — you've taken apps from zero to production, not just contributed to one layer.
• Real fluency with modern web architecture: how frontend, API, database, auth, caching, queues, and deployment fit together, and where they typically break.
• Daily, deep use of AI development tools (Claude Code strongly preferred). You drive the tool; it doesn't drive you.
• Working familiarity with a startup-friendly stack: React, Next.js, TypeScript, Node.js, Python, Postgres, and basic AWS (Lambda, S3, RDS, or similar).
• Comfort with the realities of enterprise B2B software — SSO/identity, permissions, integrations, and data customers actually depend on — or the architecture sense to come up to speed on them fast.
• Strong product instincts — you can figure out what matters and prioritize for customer value.
• A strong plus: experience shipping LLM-powered features to production — prompt design, streaming, structured outputs, evals, or agent workflows — and a realistic sense of what these systems do well and where they fail.
• High ownership, high urgency, low ego. You're comfortable being handed an outcome instead of a ticket.

This is a mid-level role. We care far more about demonstrated ability to ship complete products with AI-native workflows than about years of experience or prior titles.

You'll Thrive Here If

• You like being handed a problem, not a fully defined ticket.
• You can figure out what matters, make a plan, and start building the same day.
• You'd rather ship something useful and improve it than polish something for weeks before users see it.
• You find it hard to put an unsolved problem down, and a hard deadline energizes you rather than drains you.
• You want a stretch of your career defined by maximum output and maximum learning, surrounded by people operating the same way.
• You use AI coding tools systematically and push them hard — and you catch them when they're wrong.

This Role Is Not For Someone Who

• Needs detailed specs before starting.
• Only wants to work in one layer of the stack.
• Has only worked in narrow roles where ownership was split across many specialized teams.
• Treats AI coding tools as an occasional helper rather than the central workflow.
• Prefers process over shipping.
• Is looking for big-company pace and predictability. We're a startup in a sprint, and we're honest about it.

Interview Process

Our process is designed to evaluate real working ability without asking you to take days off or fly anywhere on spec. It has four steps:

1. Screen (45 minutes, remote). A conversation about what you've built end to end, how you think about webapp architecture, and how you actually use AI development tools day to day.
2. Live working session (2 hours, remote). A screen-shared pairing session where you work a realistic problem in our stack using Claude Code. We're not watching you type — we're watching how you drive: how you direct the AI, what you accept and reject, how you validate its output, and how you reason about tradeoffs out loud.
3. Paid mini-project (roughly one day of effort, async, on your schedule). A time-boxed, realistic product problem, compensated with a flat fee. You deliver a working repo plus a short recorded walkthrough of your decisions and how you used AI tools along the way. Evenings and weekends are fine — no PTO required.
4. In-person final (half day, Austin). Meet the team, see how we work, and make sure the setup and the people are a fit — for both sides. For remote candidates, we cover travel.

For candidates between roles or currently contracting, we can alternatively structure the final step as a paid 30-day contract-to-hire. That's an option, not a requirement.

Compensation

Full time base salary range: $105,000 to $130,000, plus benefits and any applicable equity or bonus compensation. The interview mini-project is paid a flat fee. Final compensation depends on experience, scope, and demonstrated fit.

Location

This role is based in Austin, TX, hybrid — that's our strong preference, and Austin-area candidates should be able to work in person on a regular cadence. For the right candidate, we're open to remote within the US, with occasional travel to Austin for onboarding and team time.

How to Apply

Include examples of complete webapps or products you've built — especially ones where you owned the architecture end to end. We especially want to hear how you use Claude Code or similar AI tools in your daily engineering workflow, and an example of a time you caught and corrected something the AI got wrong.