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Firmable
Free to start · No card · 5 credits the moment you sign up
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.
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.
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 new 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 automated check
Team leadership — lead 3–5 Applied AI Engineers: technical direction, code review, pairing, and growing them into engineers who own outcomes end to end
7-10 years building production data systems in business-critical environments — you've shipped systems that ran unattended, at scale, and stayed up
Worked with billions of rows — you know what breaks at that scale, and how to design quality checks that don't
Built data quality systems and frameworks — not used them, built them: validation engines, anomaly detection, scoring, sampling strategies, reconciliation against ground truth
Harness engineering experience — you've designed eval or test harnesses that other engineers depend on, and you can show the repo
Led engineers — you've directed a small team technically, reviewed their code, and stayed hands-on while doing it
Strong Python and advanced SQL — production-grade, performance-aware, comfortable with concurrency and large-scale transformations
You operate LLMs as production systems — eval sets, versioned prompts, logged traces, cost ceilings, debugged judges on precision/recall
Shipped real work with agentic IDEs — Claude Code, Cursor, or equivalent. Not "tried it" — built and shipped with it as your default mode
Sharp judgement on rules vs. LLMs — deterministic checks where structure allows, LLMs where semantic judgement is needed, and you can defend the call
B2B data: firmographics, people data, entity resolution, registry matching across markets
Cloud data platforms — Snowflake, Databricks, Redshift — and AWS for pipeline deployment
Airflow (or equivalent) orchestration at production scale
Vector databases, embeddings, or retrieval patterns for matching and deduplication
Startup or scaleup experience where you defined the standard rather than inheriting it
Firmable is an AI-native organisation. Agentic development, evals, traces, and AI-powered review are the default mode of working, not a productivity experiment. Recurring workflows ship as versioned SKILL.md specs any teammate or agent can run. Every LLM call is logged with prompt version, model, cost, and decision from day one.
We run lean and ship fast — small senior teams, no layers, minimal process, weekly releases moving toward daily. Teams own their stack end to end. There are no fixed hours and no handholding. If you're not already working this way, this role isn't right for you.
Own the trust layer — every record Firmable sells passes through systems you architect
Greenfield frameworks — the harnesses, gates, and validators are largely unbuilt; you'll define them
Frontier problems — LLM-as-judge at production scale, drift detection on vendor models, quality enforcement over billions of rows
Small team, real leverage — lead the engineers building the quality standard for 13 markets
Competitive base + meaningful equity — a share in the upside we're building toward
Firmable is an equal opportunity employer. We believe diverse teams build better products.
Ready to build the quality engine behind the world's smartest B2B sales intelligence platform? Apply now — let's talk!
Originally posted on Himalayas
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