Staff Product Engineer
Own critical parts of the platform, the customer impact, business outcomes, and make the whole team better.

About Veramatic

Veramatic builds financial automation software for automotive dealership accounting teams.

Dealership accounting is highly specialized, and much of it is still repetitive manual work: keying in data from statements and reports, checking it, reconciling accounts, and proving the numbers before they can be posted. Veramatic automates that work. Accounting rules are applied consistently, and the exceptions that need a person’s judgment are surfaced for review. The result is that accounting teams spend less time processing numbers and more time using them to run the business.

The Role

At Veramatic, Staff Product Engineers own an area and its customer impact and business outcomes. They make high-impact technical decisions, and make the team around them better.

Veramatic is hiring a Staff Product Engineer: a product engineer at heart and an architect by experience. You’ll take ambiguous, high-stakes problems where even the technology strategy may be unclear. You’ll define the goals and constraints, propose an actionable plan, and lead it from design through production and beyond. You own business outcomes and customer happiness, not just architecture diagrams.

You’ll partner with Product Management and senior leadership to shape the roadmap, and with our accounting experts to understand the domain deeply. You’ll write the code, own the AWS infrastructure, and set the standard for how the team builds with AI. Much of your impact will come through the engineers around you.

Not sure which level fits you? See Senior or Staff? Choosing your role at Veramatic.

The Problems You’ll Work On

• Connecting financial data to accurate accounting. Financial data reaches us in many ways: documents and reports in many formats today, and direct integrations with the systems our customers run their business on. We turn that data into accounting that balances to the penny. Applying AI to make this faster to build and more adaptable is a core opportunity.
• Accuracy is the product. Posting rules, reconciliations, and output formats for the many accounting systems our customers rely on. Our customers trust us with their books, so getting it exactly right matters.
• Configuration that scales. Every customer’s setup is a little different. We want onboarding and per-customer configuration to be fast, safe, and self-service.
• A platform ready for its next chapter. We’re evolving a mature platform on AWS, and we want engineers who will help decide what comes next.

What You’ll Do

• Define the direction, quality, and architecture of a critical area, such as integrations and data pipelines, accounting and reconciliation, or platform and developer productivity.
• Turn ambiguity into a plan: write design documents that frame the problem, the options, the tradeoffs, and a phased path forward, and align Product, leadership, and cross-functional partners behind it.
• Lead large releases end to end: split the work into parallel streams across engineers, integrate them into one cohesive launch, and deliver on the timeline you committed to.
• Lead platform evolution pragmatically, without slowing delivery to customers.
• Architect AWS infrastructure as code for scalability, reliability, security, and cost efficiency.
• Shape our technology choices: evaluate what we use today and decide what to keep, change, or replace, from languages and frameworks to infrastructure and AI tooling.
• Set the bar for AI-native engineering. Use AI to increase development speed and quality through intelligent automation and accuracy, so engineers spend more of their time on the human parts of development and on scalability. Design and evolve the team’s harnesses (agents, skills, MCP) so AI measurably speeds up how we build, test, and ship.
• Decide short-term versus long-term tradeoffs explicitly, spot risks early, resolve escalations, and find a path through hard situations.
• Multiply the team: mentor engineers, lead by example in code review, inform management priorities, and give reliable technical assessments in hiring.
• Remove bottlenecks: simplify code and architecture, and streamline processes so value reaches customers continuously.
• Lead by example on call, in incident response, and in post-incident learning.

What You Bring

• 8+ years building and operating production systems, including technical leadership of large, cross-cutting projects from ambiguity to launch.
• A product-engineering mindset at the highest level: you connect technical decisions to customer and business outcomes, and you’re comfortable in high ambiguity.
• A true polyglot with full-stack range. We currently use Node.js, but you’re just as comfortable in Python, Go, or another language. You’ve worked across backend, frontend, data, and infrastructure, and you have the judgment to know which tool fits and to help us decide.
• Advanced AWS knowledge. You’ve designed and owned infrastructure in code, including architecture, data stores, security, and cost, and you know when to use which.
• Deep, hands-on mastery of AI development toolchains and harnesses. You’ve built or customized harnesses (agents, skills, MCP), and you can show measurable productivity or quality gains from them.
• A record of simplifying complex systems and evolving mature codebases without disrupting customers.
• Strong data modeling and correctness instincts for systems where numbers must be exactly right.
• Excellent written communication. You write concise design documents and status updates with milestones, owners, risks, and a path forward.
• Experience mentoring senior engineers and raising a team’s engineering practices.
• You know how and when to use Slack threads, and you gently teach everyone else. 😀

Nice to Have

• Experience designing integrations and data pipelines at scale: third-party APIs and systems of record, ETL and event-driven pipelines, and document parsing and extraction, including OCR and LLM-based approaches with the evaluation harnesses that make them trustworthy.
• Experience designing configuration systems that scale.
• Experience building observability, SLOs, and incident practices from the ground up.
• Experience working in or leading distributed teams across time zones.

What Success Looks Like

• In your first week: ship to production, and start mapping the architecture, its biggest risks, and its opportunities.
• By 30 days: write and align on a technical direction for your area, including what to keep, change, or replace, and lead the first phase to delivery.
• By 90 days: your area is measurably simpler, more reliable, and faster to change, and the engineers around you ship more, with higher quality.

How We Work: Our Bar

We hire for attitude, aptitude, and first-principles thinking. We evaluate candidates on four questions: Can you do the job? Will you raise the bar? Will you strengthen our culture? Can you grow?

• Product engineers, not ticket-takers. You start from the customer problem, not the ticket. Ask why, challenge requirements when they’re wrong, and propose what’s right for the customer and the product.
• End-to-end ownership. You scope it, build it, test it, deploy it, run it, and measure it. You own the business outcome and the customer’s happiness, not just the merged PR.
• Simplify. Reduce complexity; don’t add to it. The best solution is often the one with fewer moving parts.
• Bias for action. Balance speed with correctness. Move fast in discovery, hold the line on quality in delivery.
• Insist on high standards. Yesterday’s extraordinary is today’s ordinary, especially with AI. We hold a high bar on code, architecture, and conduct, and we hold each other accountable even when it’s inconvenient.
• First-principles thinking. Remove assumptions, question the status quo, and be clear on what we’re actually trying to solve.
• Transparency. Share bad news early. Be clear about status, risk, and tradeoffs.
• You build it, you run it. Every engineer is part of the on-call rotation. Owning production is part of owning the outcome.
• Done means done. Code, tests, documentation, and logging and alerting ship together. We want to know something is wrong before a customer does.

What We Offer

• Real ownership: meaningful work end to end, from the first idea to production, with a direct line to customer impact
• Fully remote from anywhere in Latin America, with core hours that overlap U.S. time zones
• A small team with no layers and no handoffs
• Modern AI tooling, and a team that invests in learning and growth
• Colleagues who care about the craft and about each other