Tech Lead / Senior Full-Stack Engineer — AI-Enabled Data Platform

JobEgo; Paris; Sur place; EUR 90 000 - 140 000; Plein temps

Résumé du poste

Selego is seeking a Tech Lead to own an AI-enabled data platform serving institutional users. You will lead end-to-end engineering, drive architecture and technical roadmap, and maintain close collaboration with senior stakeholders and end users.

You will ship features across the data pipeline, verification workflows, and dashboards, ensuring demo-ready quality and reliability for executive reviews and investments.

Qualifications

• 5+ years of senior full-stack experience on a MERN stack with production-grade delivery.
• 8
• Extensive experience with LLM-based features: RAG, prompt engineering, context management.
• 9
• Strong English communication (C1+); client-facing experience.
• 8
• Ability to translate vague asks into a roadmap and own delivery end-to-end.
• 7
• Ownership mindset and proactive problem-solving.

Responsabilités

• End-to-end engineering leadership: architecture, code quality, sprint planning, technical roadmap.
• 2
• Direct stakeholder relationship: weekly written and verbal updates, sprint demos.
• 9
• Feature delivery on the roadmap: source verification UX, conversation context handling, scope governance, dashboards, alerts.
• 8
• Quality bar: ensure shipped features are demo-ready and trustworthy.
• 7
• Mentorship and review of junior or mid-level engineers added to the project over time.

Connaissances

Senior MERN stack

LLM features & RAG

English (C1+)

Client-facing

Ownership mindset

Outils

CRM data sources

SQL data sources

External API integrations

Description du poste

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.

Tech Lead — AI-Enabled Data Platform

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

• 30-min intro call with hiring manager.


• Technical conversation: walk through a past LLM/RAG project you led, discuss architecture trade-offs.


• Take-home or paired technical exercise (max 3 hours).


• Final round with two Selego team members and a brief intro to the project context.


• Offer.

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