Firmable is the market-leading B2B sales intelligence platform in Asia Pacific — and we're scaling that success globally at pace. Backed by leading investors and 2,000+ customers strong, we exist to give sales teams an unfair advantage: the deepest company and people data of any platform, enriched with real-time signals, served at the right moment by intelligent agents.
Our moat is the data. This role owns whether it can be trusted.
The Role
As Data Engineering Lead — Data Quality Systems, you'll lead a small team of Applied AI Engineers building the systems that measure, verify, and enforce quality across billions of company and people records in 13 markets.
This is not a QA or testing role. You won't be writing ETL test cases, app tests, or product acceptance tests. You'll be architecting the quality layer itself — verification pipelines, eval harnesses, LLM-based validators, anomaly detection, and the release gates that decide what data ships to customers.
~80% hands-on engineering. ~20% leading the team. You set the technical bar, write the hardest code,



and unblock the engineers building on top of your frameworks. If you want a pure people-management seat, this isn't it.
What You'll Own
Quality systems architecture — design and build the verification, sampling, and scoring pipelines that run continuously over billions of rows across every market
Frameworks the team builds on — the harnesses, abstractions, and SKILL.md specs that make recent quality checks fast to write, cheap to run, and hard to get wrong
Harness engineering — eval harnesses for LLM-based validation and extraction: labelled eval sets, precision/recall tracking, judge calibration, prompt versioning, drift detection on vendor model updates
Release gates — pre- and post-production gates that block bad data before it reaches customers, with the failure analysis and triage tooling to match
Incident remediation — root-cause quality incidents at scale, ship the fix, and turn the failure into a permanent

📌 Data Engineering Lead (India)
🏢 Firmable
📍 India