Engineer in Residence, AI Market Intelligence & Pricing
Summary
Build an AI-native recommendation engine and data pipeline for manufacturers as an onsite Engineer in Residence. You will prototype systems for market signal ingestion, entity resolution, and commercial workflow.
Engineer in Residence, AI Market Intelligence & Pricing
SKU-heavy manufacturers have abundant market data but struggle to turn competitive changes into commercial decisions. Price, configuration, channel, inventory, and product signals rarely connect cleanly to the company's own portfolio. This role is to build an AI-native market intelligence and pricing system that converts those signals into defensible actions.
What You'll Build
- A market-signal pipeline that ingests competitor portfolios, channel movement, pricing, specifications, and configuration changes.
- A spec-aware entity-resolution system that maps competitor products against the customer's own lineup.
- A recommendation engine that turns changes into price, positioning, promotion, or portfolio actions.
- A constraint and monitoring layer that respects cost, margin, inventory, channel, and sales realities while improving from user feedback.
What You'll Do
- Own the build from ingestion through entity resolution, signal detection, recommendations, and operator workflows.
- Work with AI Fund and enterprise users to define the first pilot, success metrics, and the MVP cut line.
- Decide which workflow ships first and keep the technical judgment behind every recommendation visible.
- Build evaluation loops for incorrect product matches, unsupported recommendations, hallucinated drivers, and constraint failures.
- Design for enterprise trust from the beginning, including data isolation, auditability, model routing, and deployment controls.
What You Need
- Strong engineering ability across backend systems, data products, AI workflows, and messy structured data.
- Demonstrated experience building GenAI systems with retrieval, entity resolution, recommendation logic, monitoring, evals, or model orchestration.
- Experience with product catalogs, pricing, taxonomy, GTM, CRM, sales-intelligence, or supply-chain data.
- Product judgment for enterprise workflows where recommendations must be explainable, constrained, and operationally useful.
- You know how to use AI coding assistants and modern AI tools to move faster without outsourcing engineering judgment.
- US work authorization. We are unable to sponsor visas for this role.
Helpful But Not Required
Experience in OEM, manufacturing, consumer electronics, commerce infrastructure, market intelligence, or channel analytics.
Experience with proactive monitoring, alerting, model routing, or production evaluation systems.
Founder, founding engineer, or senior IC experience in a B2B software company.
Who This Is For
A builder who likes hard data and workflow problems where the product must recommend an action, not merely explain a chart.
Someone who can reason about messy market signals, customer constraints, enterprise deployment, and product wedge at the same time.
What To Know Upfront
- This is a 12-week, full-time, on-site residency in Mountain View, California.
- Not every residency becomes a company. The goal is to pressure-test the idea quickly and honestly with real users and customers.
- You will be building an AI Fund idea, not bringing your own startup idea into the program.
- The process typically includes a Builder Event or equivalent working conversation, then a 48-hour Builder Challenge, then panel review with AI Fund build leadership.
- The compensation is intentionally modest during the residency because the upside, if the idea works, is a founder-level role.
Compensation
$10,000/month for 12 weeks ($30,000 total). This is a contract role during the residency. If the build leads to a funded company, the next step is a founder-level role with meaningful equity upside.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.