LH2 AI Labs
Website:
lh2.fr
Company:
https://www.linkedin.com/company/lh2-ai-labs
Seniority: Mid-Senior level
Industries: Artificial Intelligence
Job details:
Job Title: Founding Product Manager
Location: On-site, Bengaluru
Employment Type: Full-Time
About LH2 AI Labs
Built by second-time founders who have built and sold companies before, LH2 AI Labs is building the post-training infrastructure for frontier AI models.
We bring private, high-quality institutional datasets and vetted domain experts into frontier AI pipelines across verticals such as coding, computer use, agentic workflows, medical, audio, and more.
For AI to keep progressing, it needs high-quality training data drawn from real production use cases. The public web has already been crawled and trained on—there is limited new signal left there. That is where we come in.
Our vision is to create a world where frontier models can access high-quality data on tap, the same way they access computers today.
Mission
Own LH2's raw-data-to-delivery product — the buyer-facing platform that takes private institutional data from ingestion through to a finished, sellable product frontier labs can browse, sample, and license. Think AfterQuery-style data storefront, built on our pipeline.
What you'll do
- Own the product roadmap for the data-to-delivery product: how raw institutional data becomes a clean, documented, machine-trainable deliverable a lab can evaluate and take.
- Own the buyer-facing surfaces as products — the data catalog/storefront, dataset listings, method/provenance cards, sample delivery, and access-request/licensing flows.
- Be the voice of the buyer: talk to frontier labs and data-buying teams, learn how they evaluate and consume datasets, and shape the product around how they actually buy.
- Define the packaging and format standards labs expect (dataset specs, provenance/rights documentation, sample structure) and make "sellable" a clear, met bar.
- Prioritize across verticals (coding, company ops, medical, and adjacencies) so the catalog ships depth, not scattered breadth.
- Own provenance, rights-clearance, and privacy as first-class product requirements — they're the trust the whole business rests on, and they're features, not compliance checkboxes.
Must-have skills
- 5+ years in product, with real 0→1 ownership — you've defined and shipped a technical product, not just managed a backlog.
- Comfort with technical, data-heavy, or ML/AI-adjacent products; you can hold your own with researchers and engineers and translate between them and buyers.
- Strong customer-discovery instinct — you get in front of sophisticated technical buyers and extract what they actually need.
- Ruthless prioritization and the judgment to say no; you keep a small team focused.
- Clear written thinking — specs, positioning, and roadmaps that a lab and an engineer both understand.
Nice-to-have skills
- Experience in AI/ML data, developer tools, data infrastructure, or B2B data products.
- Understanding of the post-training landscape (SFT, RLHF, evals, RL environments) and what frontier labs buy.
- Experience packaging and selling to technical/enterprise buyers.
Click on Apply to know more.
