About the role
Our entire product rests on one promise: raw enterprise data goes in, and what comes out is protected to sell — nothing identifiable, nothing leaked, provably de-identified, with the audit trail to back the claim. You'll own that promise. You'll build the detection, entity-consistent pseudonymization, vault, and residual-risk gates that convert sensitive enterprise data into a trainable product buyers and regulators can trust.
This is a hands-on founding role and the most trust-critical seat on the team. The difference between a sellable product and a liability is the judgment in this role.
Responsibilities
Own the de-identification pipeline end to end: sensitive-entity detection → entity-consistent pseudonymization → residual-risk validation → clean export
Build PII/PHI/secret detection across free text, structured fields, and layout, using and extending tools like Presidio plus custom recognizers
Design and operate the vault: one durable,
namespaced surrogate per resolved entity, so the same person maps to the same pseudonym across every system (name, email, employee id, Slack/Jira/Git ids) — without token drift
Build the "rewrite all surfaces" logic that applies surrogates consistently across the dataset
Design and enforce the residual-identifier release gate (regex + NER + secret scanners + sample review) and make explicit where it does and doesn't establish legal anonymization
Enforce the trust boundary: raw stays encrypted inside the customer environment; vault keys never leave; buyers receive only the cleaned product
Build fail-closed behavior (no raw pass-through when the vault or detection is unavailable) and full audit/lineage on every reveal and export
Produce the method cards / provenance records that document de-identification technique and residual-risk posture for buyers
Design detection and compliance profiles as swappable
📌 Founding Engineer (Bengaluru)
🏢 LH2 AI Labs
📍 Bengaluru
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