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Technical Program & Product Manager - AI Economics
Bellevue, USAPosted 5 months ago
Full-timehybrid
Job Description
About the Role
The AI Economics team builds the data foundations, econometric models, and forecasting systems that power decisions across the Auger platform. Our work feeds every customer-facing application: supplier and entity intelligence, risk and compliance scoring, demand and cost forecasting, elasticity estimation, carbon and emissions modeling, tariff and trade scenarios, and the shared computation layer that lets these signals flow between products. We are the science layer of the platform, and our outputs are consumed broadly across the company.
We are hiring a Technical Product Manager to drive technical strategy, dependency management, and engineering execution across this portfolio. You will be the bridge between our scientists (economists, ML scientists, forecasting specialists) and the data and software engineering teams. Scientists produce models, methodologies, and algorithms. Engineers build the data pipelines, APIs, infrastructure, and integration points that make those models operational and consumable by other product teams. 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, why, and on what timeline.
You will partner closely with product managers across the company on customer requirements. When customer requirements involve science models, data feasibility, or technical constraints—which is most of what this team produces—you will actively shape those requirements alongside the product team rather than receive them. You own the technical and scientific viability of what gets promised to customers, and you push back when promises don't hold up against the science or the build.
A typical week might include: working with an economist to understand what data inputs a new model requires, then writing technical specifications for the data engineering team to build those pipelines; reviewing API contracts between external data services and downstream consumers; managing integration scope with external data vendors covering company, shipment, financial, sanctions, tariff, and trade data sources; identifying that a planned capability depends on a vendor integration that hasn't started; managing the science team's own roadmap and timeline commitments across multiple parallel workstreams; coordinating with product managers across the company on how science outputs will be consumed in their products and shaping those requirements where science or technical constraints apply; joining customer technical reviews when feasibility or technical scope is in question; and presenting the updated technical roadmap to leadership. You will spend significant time in the details—data schemas, service dependencies, integration points, vendor contracts, ontology extensions—because that is where cross-team misalignment creates delays. You will own the technical roadmap for the AI Economics portfolio, manage dependencies across squads and vendors, and ensure that what ships is technically sound, deliverable on schedule, and scientifically rigorous.
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 joining a Fortune 500 customer technical review 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
- Excellent written and verbal communication; ability to tailor technical content for engineers, scientists, and business stakeholders
- Experience with agile development practices and cross-functional team coordination
- Passion for using AI to speed and improve work and workflow processes