Sr. Engineering Manager

Additive AI•San Francisco, CA

5d•Onsite

About The Position

Additive builds AI-powered tools that give tax professionals superpowers. Tax and accounting is a $600B+ market with a severe talent shortage and too many manual, repetitive workflows. Our systems turn dense, often unstructured tax documents into trustworthy structured data and AI-native preparation and review experiences. The performance of the product we put in the hands of accountants is the most important metric for our team. Outputs must be trustworthy under filing-season deadlines. The cost of being wrong is high: a plausible but incorrect extraction can waste hours of professional review, misstate a tax position, or flow into a filed return. We use extensive in-house datasets, rigorous evaluation suites, and deep, collaborative customer partnerships to decide what is ready to ship and where to invest next. As part of Thomson Reuters, we pair startup speed and individual ownership with deep tax expertise, established customer relationships, and a path to rapidly deploy into real tax workflows at scale. In this environment, our team can build quickly, learn directly from customers, and distribute what works. Today, Additive products are used daily at scale by many of the biggest accounting firms in the country. We are hiring a Senior Engineering Manager to be a hands-on player-coach for one of Additive’s engineering teams. You will directly manage a team of 4-6 that will grow up to 10-12 engineers, primarily at the staff and principal level, while remaining an active technical contributor. You will be especially close to the code during your first three to six months as you build context and credibility. Our engineers own outcomes end to end, from understanding a tax professional’s workflow to rollout and measurable customer impact. Your role is to raise the technical and product bar, develop exceptional engineers and future leaders, and help the team move quickly without becoming its decision-making hub. We measure leadership contribution by team output, customer impact, and talent density, not headcount or hierarchy.

Requirements

Written meaningful production software within recent years and can still review a design, read a pull request, debug a difficult issue, and hold your own in a technical debate with a senior engineer.
Directly managed experienced engineers while continuing to contribute technically, with a track record of improving both individual growth and team output.
Shipped customer-facing, eval-driven products and connected engineering decisions to adoption, trust, revenue, or operational outcomes.
Strong product and customer judgment, including experience connecting engineering decisions to adoption, trust, revenue, or operational outcomes.
Experience in both operating with startup urgency as well as navigating the stakeholders, governance, security, and dependencies of a larger enterprise.

Nice To Haves

Experience with Python, TypeScript, cloud infrastructure, agentic or retrieval-based systems, document AI, tax technology, or enterprise data products.

Responsibilities

Build and ship. Contribute directly to technical design, implementation, debugging, testing, and release work. Stay fluent in the codebase and step into the highest-leverage technical problems without becoming the team’s bottleneck. Guide effective AI-driven development throughout all aspects of the development lifecycle. Choose the pragmatic, boring option when that ships reliable value to customers faster.
Develop exceptional engineers. Set clear expectations, give direct and personal feedback, coach technical and product judgment, address performance or interpersonal issues early, and help engineers grow into larger leadership roles.
Make evals part of product development. Establish and refine what we measure, why it matters, and how evaluation signals become release decisions, product priorities, and durable regression guardrails. Turn production failures and customer feedback into representative test cases, datasets, and metrics.
Turn strategy into owned outcomes. Define clear finish lines, ownership, milestones, and lightweight operating rhythms. Improve forecasting, surface risk early, and preserve flexibility in how engineers solve problems.
Stay close to customers and the product. Spend time with tax professionals and customer-facing teams, understand their workflows, and make sound product calls when there is no product manager in the room.
Grow a high-talent-density team. Own hiring, candidate assessment, closing, onboarding, and interviewer calibration. Create an environment where exceptional individual contributors want to work and where adding people follows impact, not empire building.