Senior Software Engineer - Dev Tools

Senior Software Engineer - Dev Tools

Full-time · Engineering · San Francisco, CA (3 days/week in office)

A dev tools engineer to bring agentic workflows into our development stream - code review, investigation anddebugging, refactoring, testing - measured on delivery metrics, not demos.

This role is different from our others: your customers are the engineers here, and the product is how fast and howwell they ship.

We believe agentic workflows belong inside the development stream itself, not just in the editor. Code review,investigation and debugging, refactors, test generation and maintenance, and answering the engineering team'sday-to-day questions are all loops that can be built, run, and improved. You'll own building them - and owningthem means the unglamorous parts too: keeping them reliable, knowing when one is doing more harm than good, andretiring the ones that don't earn their place.

The bar we hold this work to is evidence. We want measurable movement in how this team delivers software - cycletime, review latency, change failure rate, time to recover, build and test reliability, time lost to environmentand CI problems. Part of the job is instrumenting the development pipeline well enough to know where the timeactually goes, establishing the baseline before changing anything, and being honest about what moved and whatdidn't. Enthusiasm for AI tooling is necessary here. It isn't sufficient, and it isn't the deliverable.

You'll work closely with our infrastructure team to keep CI fast and dependable, since none of the rest of itmatters if the pipeline is red or slow.

What You'll Do

• Build and operate agentic loops across the development stream - code review, investigation and debugging,refactoring, test generation and maintenance, and an engineering help desk that answers questions about oursystems
• Instrument the development pipeline end to end, so we have real data on where engineering time goes rather thananecdotes
• Establish baselines and own the metrics that define success in this role: cycle time, review latency, changefailure rate, time to recover, build and test reliability
• Evaluate new tools and models against our actual codebase and workflows - run the comparison, measure theresult, and make the call to adopt, park, or drop
• Partner with our infrastructure team on CI: build and test times, flakiness, capacity, and the reliability ofthe pipeline everyone depends on
• Build the guardrails that let agents operate safely in a regulated codebase - permissions and least privilege,secret handling, provenance and review requirements for generated changes, and an audit trail of what wasautomated
• Improve the underlying substrate agents depend on: repository structure and conventions, test coverage andspeed, internal documentation, local and ephemeral development environments
• Work within the tooling and workflows the team already has - support them, extend them, and make them better,rather than replacing them by default; when a replacement is genuinely warranted, own the case for it and themigration that follows
• Work directly with the engineering team to find where they're actually losing time, and to make sure what youbuild gets used
• Write production code in Python, and in TypeScript where our application codebase requires it
• Participate in business-hours on-call rotation shared across the engineering team (no nights/weekends)

How We Work

We don't have product managers. You'll find the problems yourself by watching how this team works, decide what'sworth building, and defend the tradeoffs - that discovery is part of the job.

This is a build-and-measure role, not an evaluation role. We expect strong opinions about AI tooling and we expectthem to be tested: shipped into the workflow, instrumented, and kept or killed on the evidence. A loop that looksimpressive in a demo and quietly wastes reviewer attention is a failure, and part of your job is being the personwilling to say so.

You're also joining a team that already has tools and habits it relies on. Those are the starting conditions, notobstacles. We're looking for someone who can make the existing environment work better before proposing to changeit, and who understands that switching costs are real and fall on other people.

Qualifications

Required

• 10+ years of professional software engineering experience, including substantial time writing productionapplication code - you have to be credible to the engineers you're building for
• Experience building internal developer tooling, developer platform, or build and release systems where otherengineers were the users
• Hands-on experience building with LLMs and agentic tooling beyond everyday assisted coding - orchestration, tooland context design, prompt and workflow iteration, evaluating output quality systematically
• Strong CI/CD depth: pipeline design, build and test performance, flaky test diagnosis, artifact and dependencymanagement
• Demonstrated use of measurement to drive engineering outcomes - instrumenting a process, establishing abaseline, and showing what changed
• Strong Python, and the ability to work in a TypeScript codebase
• Ability to track a field that is moving quickly and separate what is genuinely useful from what is merely new
• Exceptional communication and influence without authority - adoption is voluntary, and tooling nobody uses isworth nothing
• Track record of improving an engineering environment you inherited, meeting a team where its tooling andworkflow already are
• Comfort with ambiguity and a habit of teaching yourself the domain
• Low-ego approach and a high bar for precision
• Based in the SF Bay Area with the ability to work in-office 3 days per week

What Makes You Stand Out

• Experience building evaluation harnesses or benchmarks for LLM output, especially against a real codebase
• Experience authoring MCP servers or designing tool interfaces for agents
• Experience running a developer productivity or platform function, including DORA or similar metrics programs
• Large-scale automated refactoring experience - codemods, AST tooling, static analysis
• Test infrastructure depth: flake reduction, test selection, parallelization, coverage strategy
• Security or compliance awareness around AI in the SDLC - code provenance, data handling, third-party model risk
• Startup experience on small engineering teams (<10 people)

Technical Environment

• Backend: Python
• Frontend: React/TypeScript
• Database: PostgreSQL
• CI/CD: GitHub Actions
• Cloud: AWS

Why Join Us?

• Leverage: Your work compounds across everything the engineering team ships
• A real mandate: This is a funded, owned function, not a side project someone runs between features
• Ahead of the curve: Agentic development workflows are being figured out right now, and you'd be doingthat work rather than reading about it
• Direct Influence: Small team, flat organization, direct access to leadership
• Unique Domain: Support engineers building first-of-their-kind Bitcoin-denominated financial products
• Benefits:
  • Fully covered health, dental, and vision for you and your family
  • Meals provided in office
  • Two annual company off sites (fully paid)

Our Values

• Keep your word. Honor commitments to clients and each other.
• Build for the future. We measure success in decades; look ahead without losing sight of what matterstoday.
• Be curious. Our advantage is understanding the world, the market, and each other.
• Have fun. Enjoy the work. Find humor where you can. Rest when needed. Say when you need help.

Company & Funding

We're building the world's largest long-term insurer, using digital money and AI to serve billions of peopleprofitably. We want anyone, anywhere, to be able to save for their future, protect their family, and buildwealth across generations.

We face a once-in-a-century opportunity to build a vertically integrated life (re