Head of Engineering - AI Document Intelligence

Read this first — Requirements
If any of the following are not true for you, please don't apply. We will verify these.

1. 5–10 years of professional engineering experience, with at least 3 years in a hands-on technical leadership role (Head of Engineering, Engineering Manager, Tech Lead, or Founding Engineer with hiring authority).
2. You have built and managed engineering teams before. You have hired senior engineers yourself, set up code review / on-call / shipping processes, run performance conversations, and owned a technical roadmap.
3. You have deep, production-grade document processing experience. You have personally shipped systems that ingest and extract data from diverse real-world documents at scale — PDFs (including large multi-thousand-page packages), scanned images, email containers, Office files, and archives. You can speak in detail about the failure modes, monitoring strategies, and architectural tradeoffs involved.
4. You are a player/coach. Roughly 40% of your time will be hands-on (architecture, code review, hard production problems, occasional coding on critical work). Roughly 60% will be leadership (hiring, 1:1s, roadmap, cross-functional, culture).
5. You are USA-based and willing to work hybrid. If you are not local to our hub, frequent travel to the office will be required.
6. You are comfortable with startup intensity. This is not a 9-to-5. Core hours are 8am–5pm with regular evening and weekend work expected.

About the Role
You will be the most senior engineering hire at Wamy, reporting directly to the founder. You will lead the current engineering team and grow it to 5–10 engineers within your first year. You will own the engineering roadmap and be personally accountable for the reliability, quality, and pace of every system we ship.
This is a deeply technical leadership role. We need someone who has actually built document processing pipelines at scale — not a manager of doc AI engineers from a distance — because the hardest problems on our roadmap are document problems, and the engineers under you will look to you to set the technical bar.
What you'll own

Document pipeline reliability and architecture. OCR routing, format detection and conversion, large-file handling, splitting and chunking strategies, queue design, retry and idempotency logic, observability, and quality monitoring. You'll set the standards and write the post-mortems when things break.
AI systems strategy. Multi-model orchestration across providers (OpenAI, Google Gemini, Anthropic), task-based routing, graceful fallback under provider degradation, RAG retrieval quality, and the eval infrastructure that keeps our AI shippable.
Engineering hiring and team building. You will hire two to five engineers in your first year. You will set the bar for what "good" looks like in interviews, design our technical screen, and build the culture of ownership and shipping speed we already have.
Roadmap and shipping cadence. You will partner with the founder on what to build, when, and at what depth. You will keep our roughly-twice-a-week shipping cadence alive as the team scales.
Production reliability. On-call rotation, incident response, monitoring, SLOs. You own the systems that keep our customers' work moving.
Cross-functional leadership. Direct collaboration with the founder, customer-facing teams, and design partners. You will translate customer pain into engineering priorities — and translate engineering reality back into product timelines.