Staff Software Engineer, AI & Automation

The AI Knowledge team owns the surface that makes Gladly's AI actually useful. Our AI is only as good as what it can see and what it can do, and we control both. We build the integrations that give the AI real-world context (customer data, product catalogs, external systems) and the integrations that let it take action on a customer's behalf. If the AI can look up an order, check inventory, or trigger a return, our team built the path.

We provide all the Knowledge and Connectors that our AI needs to be effective. We are a small, senior team that ships fast, debates openly, and goes deep on root causes. We over-communicate, we care about the craft, and we expect a lot of each other. If you want a front-row seat to how AI gets applied in a real product at real scale, this is the team.

We are looking for a Staff Software Engineer, ideally bordering on Principal, to be the most senior individual contributor on the AI Knowledge team. This is a deeply technical, high-autonomy seat, not a management role. You will own the full connector and knowledge surface that feeds Gladly's AI, and you will set the direction for how that surface evolves over time.

Your first six months will likely center on two things: making the actions our AI can take easier for customers to configure and extend, and building tooling that lets customers stand up new integrations without writing custom code. You will work shoulder to shoulder with product, design, and customer-facing teams, and you will have real customers on the other end of your decisions.

You are the kind of engineer who owns problems end to end, keeps digging when everyone else has accepted an answer, and raises the bar of the team around you without being asked. You are comfortable moving between domains, you enjoy mentoring, and you use AI coding tools every day because they make you faster, not because it is trendy.

• Own the integration architecture. Set the technical direction for how external systems connect to Gladly's AI. Evolve what exists, design what doesn't, and know when to do which.
• Build the connective tissue for AI. The LLM needs context to be useful and pathways to take action. You will build both, expanding what the AI can see and what it can do across the customer's full tech stack.
• Solve product-level problems, not just technical ones. Partner with product and design on how integrations should feel for customers, not just how they work under the hood. Your work does not stop at the API boundary.
• Ship at a high bar, fast. Features go from idea to production with direct input from customers like Crate & Barrel and REI. You will build, iterate, and ship, not design in a vacuum.
• Mentor and raise the bar. Demo your work, share what you learn, and help Senior engineers grow into Staff. You will be the senior technical IC the rest of the team looks to.
• Collaborate across the company. Work closely with product managers, designers, and customer-facing teams to solve problems that matter to the business.

• 8+ years of full-stack engineering experience with a track record of shipping large-scale product. Comfortable across the stack.
• Proven Staff or Principal-level ownership. You have owned domains end to end, made architectural decisions independently, and driven projects to completion with minimal oversight.
• Daily, hands-on use of AI coding tools (Copilot, Cursor, Claude, or similar) as part of how you build. You have opinions on where they help, where they get in the way, and when to override them.
• A strong track record of turning ambiguous ideas into shipped product, especially in 0-to-1 settings.
• Deep experience with, or real willingness to learn, TypeScript, React, Go, and PostgreSQL.
• The ability to go deep on root cause rather than stopping at the first plausible answer. You are the person others bring the hardest bugs to.
• Strong communication skills. You can zoom out and explain a system at a high level of abstraction, and zoom in and debug a specific behavior in the code.
• A customer-centric mindset. You care about what you are building and who you are building it for.

Bonus Points For

• Experience building integration platforms, API ecosystems, or developer-facing tools
• Familiarity with protocols like MCP (Model Context Protocol) or similar LLM integration patterns
• Hands-on experience with LLMs (OpenAI, Claude, etc.), embeddings, or vector search in production
• Familiarity with operational tools like DataDog, SumoLogic, and LangSmith
• Open source work, public talks, or thought leadership in AI or engineering

Compensation

$183,000 to $246,000 annual salary + equity + benefits 

For cash compensation, we set standard ranges for all U.S.-based roles based on function, level, and geographic location, benchmarked against similar-stage growth companies. In order to be compliant with local legislation, as well as to provide greater transparency to candidates, we share salary ranges on all job postings regardless of desired hiring location. Final offer amounts are determined by multiple factors, including geographic location as well as candidate experience and expertise, and may vary from the amounts listed above.