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Salary
≈ $25k – $57k per year (Estimated)
Location
In office (Bengaluru)
Seniority
Staff · 8+ years exp

First seen by Alion on Oct 1, 2026.

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LH2 AI Labs builds frontier data infrastructure: licensed datasets, RL environments, and expert talent for AI labs.

About LH2 AI Labs :

LH2 AI Labs is an applied research lab solving data platform and curation challenges for foundation model development. We serve every frontier AI lab with the mission of delivering the best data to power the best models.

Our customers are the ones building the foundation models themselves and our work sits directly in the loop of how those systems improve. This is a rare opportunity to join a company at a defining moment in AI.

About the role :

This is a full-time, hands-on role where you will own the core infrastructure and systems that enable us to discover customers' data landscape, handle sensitive data like names, address securely and to clean and catalog them into training-ready datasets.

That path covers connectors and on-prem agentic discovery components, secrets and PII scrubbing, scale and cost efficient ingestion and clearance for use in model training. You lead a small team of 3-4 engineers and raise the quality bar in your pod.

What you'll own :

1. Connectors and extraction :

- You'll build connectors for common SaaS and databases (Google Workspace, Slack, Postgres/MySQL, Jira, MongoDB) and for specific tools such as Razorpay, GreytHR, Keka, Zoho and LeadSquared. The rule is to build only where no good open-source connector or clean export exists.

2. On-prem scanning :

- You'll build a CLI or agent that runs at the data owner's end to sample and estimate the value of their data without shipping all of it to us.

3. Clearance pipeline :

- Secrets detection across full git history, fail-closed. PII redaction for code and conversational data, including Indian identifiers (PAN, Aadhaar, GSTIN, IFSC, UPI). Measurable recall and precision.

4. Lineage :

- Every output record must trace back to its raw source, and every lot must be revocable.

5. Delivery :

- Packaging, sampling for buyers, and supporting the supply and BD teams on data questions.

You have :

Experience :

- 8 - 12 years in backend or data engineering, with at least 2 years leading up to 4 or more engineers.

Pipeline development :

- You've built ingestion or ETL pipelines that run in production.

Sensitive data handling :

- Hands-on work with sensitive data such as PII, financial or health data, including redaction, masking or access controls.

Technical judgment :

- The judgment to decide what to build and what to adopt.

Nice to have :

- Experience with Presidio, gitleaks/TruffleHog, dlt or Airbyte.

- Knowledge of DPDP, GDPR, HIPAA or SOC 2.

- You've shipped software that runs in customers' environments.

This is not a pure people-management role. You'll write code, review everything, and personally own the hardest problems in the pod.

Skills

Data Engineering, ETL, Data Privacy Management, Data Ingestion, Data Services, Data Management, SaaS, PostgreSQL

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