Founding Engineer - Avery

• Build and own ETL pipelines that make our candidate, hiring, and market data reliable, accessible, and production-ready
• Dig into the data - surface patterns, catch quality issues, find what's missing
• Establish data quality standards and monitoring so everything downstream is built on a trustworthy foundation
• Identify data gaps and either acquire what's needed or make the case for it

AI-Powered Platform (30%)

• Build full-stack features from backend logic to polished UI - we ship things people actually use
• Architect for scale: clean, well-tested, maintainable code that doesn't become tomorrow's problem
• Improve the agentic workflows powering our sourcing, screening, matching, and market intelligence systems
• Bring engineering judgment into product and UX decisions - you'll have a seat at that table

Predictive Hiring (20%)

• Define what labeled datasets look like for our domain - what does "good match" actually mean in data terms?
• Assess whether our data can support predictive models: candidate-role fit, response likelihood, time-to-fill
• Where the data supports it, build and iterate on fine-tuned models end-to-end - from exploration to production
• Own the data & AI roadmap alongside the interim CTO/CPO, * Founding-level influence: Technical direction, data strategy, product decisions - you'll shape all of it.
• Equity-first: Substantial equity for someone who wants to build long-term value, not just collect a salary.

Do you have experience in TypeScript?, Must-haves

• Strong data engineering background: ETL pipelines, data infrastructure, analysis at scale
• Full-stack ability: comfortable across React, TypeScript, Next.js, Node.js - not just notebooks
• Hands-on AI/ML: LLMs, embeddings, RAG, fine-tuning, prompt engineering
• Data science fluency: statistical modeling, building labeled datasets, knowing when data can and can't support a model
• Familiarity with: OpenSearch, Apache Spark, AWS, Inngest, Railway, Mastra or similar agentic frameworks
• Uses AI-assisted development tools (Claude Code, Codex, etc.) as a matter of course

The mindset that matters more than the stack

• Gets excited about messy data - finding signal where others see noise
• Ships. Doesn't wait for perfect conditions
• Thinks in products, not just systems - cares whether what gets built actually helps someone
• Comfortable with ambiguity and building in an early-stage environment where the roadmap evolves

• Competitive salary: Equity is the focus, but the package is fair.
• Something worth building: Companies make better hires. People land better roles. The impact is real.