Tech Lead — AI-Enabled Data Platform

About Selego

Selego is a digital product studio building tech solutions for ambitious clients across sectors including healthcare, public sector, education, and corporate. We take ownership of products end-to-end: discovery, build, and ongoing iteration.

The project

We are looking for a Tech Lead to take ownership of a strategic engagement in the data intelligence space. The product is a live, AI-enabled data platform serving institutional users (investors, consulting firms, industry analysts). It is currently in production and used daily by senior decision-makers.

The platform combines:

• A proprietary structured dataset (companies, deals, investments, market analysis).
• A multi-source RAG pipeline indexing structured data, articles, presentations, and transcripts.
• A multi-LLM backend (Claude, OpenAI, Gemini, Vertex) with chunking, streaming, and cost tracking.
• A React front-end with chat, dashboards, and admin tooling.
• A daily ingestion pipeline from CRM, SQL sources, content platforms, and meeting transcripts.

The product is also being evaluated as a resaleable offering. The Tech Lead will play a central role in raising product quality from "good internal tool" to "demo-able to a senior decision-maker without preparation".

What you'll own

• End-to-end engineering leadership: architecture, code quality, sprint planning, technical roadmap.
• Direct stakeholder relationship: weekly written and verbal updates, sprint demos, key meetings with senior teams and end users.
• Feature delivery on the existing roadmap: source verification UX, conversation context handling, scope governance, account-health dashboards, deal alerts, confidence scoring, and more.
• Quality bar: ensure shipped features are demo-ready, sourced, and trustworthy enough to put in front of a senior consultant or PE investor.
• Mentorship and review of any junior or mid-level engineers added to the project over time.

Profile we are looking for

Must-haves

• Senior full-stack experience (5+ years) on a MERN-style stack (React, Node.js, MongoDB). Comfortable across front-end, API, and data layer.
• Real production experience with LLM-based features: RAG, prompt engineering, tool use, context management, eval design. You have shipped at least one AI feature to real users and know how to debug it.
• Strong written and spoken English (C1+). The user base operates in English; you will run client-facing calls and write deliverables directly. Native or fully fluent.
• Client-facing maturity. You can present, take feedback, push back diplomatically, and translate vague asks into a roadmap.
• Ownership mindset. You see a problem, you scope it, you ship it. You don't wait to be told.

Strongly preferred

• Domain understanding in a regulated, data-heavy vertical (finance, legal, life sciences, healthcare). This is a meaningful accelerator.
• Experience working with consultants, analysts, or PE/investment professionals as end users. You understand that they need to verify everything before citing it.
• Comfort with CRM data, SQL data sources, and external API integrations.

Nice to have

• French is a plus for internal collaboration but not required.
• Prior experience in a product studio / agency setup, juggling deliverables with product thinking.
• Experience with vector databases and embedding models.

How we work

• Small, focused teams (typically 2-4 engineers per project).
• Direct contact for senior engineers, not filtered through PMs.
• Pragmatic engineering culture: ship working software fast, refactor when patterns emerge, no premature abstraction.
• Code reviews, written docs, but no excessive process. We hire seniors and trust them.
• Tooling: GitHub, Slack, Notion, Linear.

Compensation

To be discussed depending on profile and contract type (CDI vs freelance). Competitive for the Paris market.

Process

1. 30-min intro call with hiring manager.
2. Technical conversation: walk through a past LLM/RAG project you led, discuss architecture trade-offs.
3. Take-home or paired technical exercise (max 3 hours).
4. Final round with two Selego team members and a brief intro to the project context.
5. Offer.

Target: 2-3 weeks from first call to offer.

To apply: send CV and a short note about a project you led where you had to ship an AI feature to real users.