Senior Fullstack Engineer, Fetch

• 4+ years of hands-on fullstack engineering experience in a medium to large engineering environment
• Strong backend experience, ideally in Python
• Working experience with modern frontend development and the ability to contribute confidently to Svelte or a comparable framework
• Comfort owning work across the stack: product features, service integration, and the implementation details in between
• Solid grounding in distributed systems or systems-level engineering concepts
• Strong written and verbal communication, including the ability to explain a tradeoff to someone who doesn't share your context
• Demonstrated ability to work independently, navigate ambiguity, and drive work to completion without every task assigned
• Track record of collaborating effectively across backend, frontend, and machine learning disciplines
• Interest in using AI tools and agentic workflows to improve engineering speed, quality, and maintainability

Desirable

• You'll join the team that builds FAST, Fetch's internal AI analytics platform
• FAST puts an analytics agent in front of business users so they can answer real data questions in plain language instead of waiting in a queue for an analyst
• It's also a product that has to earn the trust of people who will not tolerate a wrong number
• This is a fullstack role centered on the product around the agent
• You'll build and own new features, new integrations, and the services and interfaces that turn a capable agent into something people rely on day to day
• The work spans the stack but leans towards backend
• We're a small team, and you'll own the features you ship
• Engineers here upskill one another across domains, and AI-assisted workflows have made that ramp faster than it has ever been
• You'll work alongside fullstack and ML engineers building a product that serves Fetch
• Over time, and depending on where the platform goes, there's a path into the agent layer itself: evals, capability expansion, and the accuracy work that determines whether any of this succeeds
• Design, build, and ship product features across the FAST platform, with the majority of your work in Python services and APIs
• Own backend-dominant fullstack work end to end, including the Svelte frontend surfaces that expose it
• Build the data models, integrations, and service architecture that turn a working agent into a product people rely on
• Improve FAST's reliability, maintainability, and architecture
• Raise the bar on backend and product engineering craft within the team through code review, design discussion, and hands-on pairing
• Bring clear tradeoff thinking to design and architecture decisions, and turn ambiguous product needs into concrete implementation plans
• Improve how the team ships, including where AI-assisted workflows meaningfully improve quality and speed