Full Stack Developer​/AI Focused

About Us

We are a fast-growing technology company building products used by hundreds of thousands of customers, backed by a supply chain spanning multiple distribution centers and a data platform processing millions of events daily. Engineering is not a support function here — it is a core driver of every major business outcome.

We move fast, hold ourselves to a high bar, and believe the best engineering decisions are made by people who are close to the business. We are embracing AI not as a trend, but as a genuine multiplier — using it to ship better software, faster, while never losing sight of the craftsmanship that makes software great.

This is a forward-deployed engineering role with AI at its core. You will architect systems, write production-grade code, design databases, and own your projects end to end — with a primary focus on deploying AI capabilities directly into the business and products that serve real users. What defines this role is the expectation that you bring strong engineering fundamentals together with a hands‑on, deployment‑first mindset for AI‑powered tools and workflows.

You are not required to be an AI researcher or an ML specialist. You are expected to be an excellent engineer who deploys AI where it creates real value — using it to accelerate delivery, build intelligent features, and solve hard problems, while applying your own judgment to validate, refine, and own the outcome.

• Design robust, scalable systems from the ground up
• Write clean, well‑tested, maintainable code
• Optimize database performance and data models
• Debug complex issues across the full stack
• Own code quality through rigorous peer review
• Deliver reliable software with measurable outcomes

• Use AI coding assistants to accelerate development
• Leverage LLMs to generate boilerplate, tests, and docs
• Build AI‑powered features where they add real user value
• Apply AI to improve code review, debugging, and analysis
• Evaluate AI outputs critically – judgment still wins
• Stay current and bring new AI tools to the team

• Outcomes over activity — we measure what ships and what works.
• Speed is a feature — long approval chains kill great products.
• Radical candor — honest feedback is a form of respect.
• Learning is non‑negotiable — every sprint is a chance to improve.
• No politics, no silos — collaborate openly across every team.

• Fast‑paced sprints with a strong bias toward shipping.
• Engineers own requirements, architecture, and roadmap input.
• AI tools are standard kit — we share what works.
• Blameless post‑mortems — failure is a learning event.
• Async‑first with intentional synchronous collaboration.

• Design, build, and maintain scalable, high‑quality software systems and APIs that serve real users in production.
• Write clean, well‑structured code with appropriate test coverage — unit, integration, and end‑to‑end.
• Architect and optimize relational and non‑relational database schemas, queries, and data models for performance and reliability.
• Conduct meaningful code reviews that improve team quality and share knowledge, not just catch syntax errors.
• Debug, profile, and resolve performance bottlenecks and production issues with urgency and rigor.
• Contribute to technical architecture decisions — propose solutions, evaluate tradeoffs, and document outcomes.
• Participate actively in Agile ceremonies: sprint planning, standups, retrospectives, and backlog refinement.

• Deploy AI solutions end‑to‑end — from identifying the right use case, to building and shipping LLM‑powered features directly into products and internal workflows.
• Incorporate LLM APIs and AI frameworks into product features where they create genuine user value: search, summarization, recommendations, intelligent automation, and decision support.
• Apply critical engineering judgment to evaluate, refine, and validate all AI‑generated outputs before they reach production — you own the result, not just the prompt.
• Use AI coding assistants (Git Hub Copilot, Cursor, Claude Code) as a daily accelerator — and champion effective AI tool patterns and prompt…