Build at Auger Auger is the autonomous operating system for supply chains. It connects enterprise supply chain systems—ERP, WMS, TMS—into a single data layer, then uses AI to detect problems, evaluate trade-offs, and execute decisions automatically. The platform eliminates the coordination tax: the time and capital lost when disconnected systems force humans to become the integration layer between planning and execution. Actions that previously required days of meetings and manual coordination happen in seconds, within constraints the customer defines.

Founded by Dave Clark and backed by $100M from Oak HC/FT. Headquartered in Bellevue, Washington.

About The Role The AI Economics Team at Auger is building an AI and agentic-powered market intelligence system that enables our customers to forecast supply chain risk, optimize sourcing decisions, and respond to global disruptions in real time. We are hiring a Technical Product Manager to drive organization, technical strategy, and engineering execution across this initiative.

You will be the bridge between our scientists (economists, ML scientists, forecasting specialists), software engineers and data teams. Scientists produce models, methodologies, and algorithms. Engineers build the data pipelines, APIs, infrastructure, and user interfaces that make those models operational. Your job is to translate between these groups—turning a causal inference framework into engineering requirements, turning infrastructure constraints into scope decisions for the science team, and keeping both sides aligned on what we're building and why.

A typical week might include: working with economists to understand what data inputs a new supplier risk model requires, then writing technical specifications for the data engineering team to build those pipelines; reviewing API contracts between external data services and the frontend dashboard; identifying that a planned feature depends on an external data vendor integration that hasn't started; and presenting the updated roadmap to leadership.

You will spend significant time in the details—data schemas, service dependencies, integration points—because that is where cross-team misalignment creates delays. You will own the product roadmap across a suite of science-and-economics-driven products, manage dependencies between squads, and ensure that what we ship solves real customer problems.

Auger is an AI startup. You will operate with limited resources, shifting priorities, and incomplete information. We need someone who thrives in ambiguity—who can make decisions with 70% confidence, adjust when wrong, and maintain forward momentum without waiting for perfect clarity. You should be comfortable writing detailed technical specifications one day and presenting to enterprise C-suite the next.

What You Bring

• 7+ years of product management experience, with at least 4 years on data-intensive or ML-adjacent products
• Experience translating analytical or scientific requirements into engineering tasks—you've worked with data scientists, analysts, or researchers and turned their work into shipped software
• Experience shipping a successful data analytics or ML product to market
• Understanding of data infrastructure concepts: ETL/ELT pipelines, data warehouses, feature stores, API design, and how data flows through production systems
• Track record of managing complex cross-functional projects with multiple dependencies and competing priorities

Compensation & Benefits As part of our commitment to People Powered Greatness, we invest in our team members with competitive compensation and a comprehensive benefits to support your health, financial future, and daily life. The package includes medical, dental, and vision coverage, a 401(k) with company match, and commuter benefits. Total compensation may include a combination of a competitive base salary and equity. Your initial placement within our salary range will be based on your experience, qualifications.

The base pay range for this role is $180,000 – $250,000 per year.

Auger considers all qualified applicants for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.