Engineer in Residence: MarketRadar
On-siteMountain View Santa Clara County, California, United States
Job Summary
Build a synthetic market-signal pipeline that ingests competitor portfolio data, channel movement, and pricing changes to drive commercial actions for OEM teams. Own the technical build from data model and ingestion through entity resolution, recommendation logic, and operator workflow, working directly with AI Fund's build team and enterprise users to pressure-test the wedge. Decide which workflow ships first, including competitive portfolio remapping or win/loss intelligence, while designing for enterprise trust with data isolation and auditability. Ship a working prototype in weeks using synthetic data to test founder-market fit before a potential founding role at the spun-out venture.
Required Qualifications
- Strong hands-on engineering ability across backend systems, data products, and AI-native workflow software
- Experience with messy structured or semi-structured data, such as product catalogs, SKU normalization, taxonomy mapping, pricing data, GTM data, sales enablement systems, CRM data, or supply chain signals
- Judgment about entity resolution, recommendation systems, monitoring, evaluation, and model orchestration
- Comfort building for enterprise buyers where security posture, audit trails, and deployment trust matter from day one
- Evidence that you can use AI coding assistants and modern AI tools to move faster without outsourcing engineering judgment
- US work authorization
- Founder-level curiosity about the customer workflow, not just the model or dashboard
- Someone who can reason about messy market signals, customer constraints, enterprise deployment, and product wedge at the same time
- A builder who sees the opportunity to turn competitive intelligence into an OEM-native action system
Desired Qualifications
- Experience in OEM, manufacturing, consumer electronics, commerce infrastructure, retail pricing, catalog systems, market intelligence, competitive intelligence, sales intelligence, RevOps data products, or channel analytics
- Experience building agentic monitoring, proactive alerting, eval harnesses, model routing, open-source model deployment, or token-cost optimization in production
- Experience with category planning, commercial strategy, pricing optimization, product taxonomy, SKU enrichment, win/loss analysis, or supply chain visibility
- Founder, founding engineer, or senior IC experience in a B2B software company
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