AI Engineering Lead

Eggai; France; Remote; EUR 120,000 - 180,000; Full time

Job summary

Eggai is seeking a senior leader to drive the design, development, and deployment of production-grade AI systems for enterprise clients. You will lead a small remote team, own architecture across agents and data, and ensure production readiness while guiding clients through adoption and measurable results.

Responsibilities include building critical agents and evaluation infrastructure, establishing governance and controls, and turning successful approaches into reusable assets for future

Qualifications

• Experience designing, shipping, and operating production-grade AI systems.
• Ability to lead small engineering teams and communicate across stakeholders.
• Strong coding skills in Python or TypeScript/JavaScript.
• Experience with AI tooling, evaluation infrastructure, or data assets.
• Open-source contributions or AI community involvement.

Responsibilities

• Act as a trusted technical counterpart to client teams.
• Own solution design and system architecture across agents, tools, data, evaluations, controls, human oversight, and deterministic boundaries.
• Build the system's critical agents, integrations, evaluation infrastructure, permissions, observability, controls, and feedback loops.
• Deliver: Lead the team and client from implementation through adoption, owning engineering quality and production readiness.
• Package successful work as tools, datasets, evaluations, patterns, and engineering methods.

Skills

AI systems design

Technical leadership

Production-grade coding

Python

TypeScript/JavaScript

Experimentation

Communication

Tools

Python

TypeScript

Job description

the company · Full-time · Remote (EU only)

The RoleYou will lead a small, highly-skilled remote team of engineers designing and shipping production-grade agentic AI systems. Working directly with enterprise clients, you will validate where AI can create value, redesign business processes, and own the resulting system from early experiments through adoption and measurable results.

Across these environments, you will learn from recurring production failure modes and have the latitude to choose the models, tools, and architecture to solve the business problem.

Alongside client delivery, you will turn successful approaches into shared assets that strengthen future engagements. Those contributions will shape the company's engineering culture and give you broad influence over how we work.

This is a hands-on leadership role. You will write production code, set technical direction, develop engineers through example, review, feedback, and coaching, and guide senior client stakeholders through difficult decisions.

This is a remote position. We only accept candidates located in the EU.

What You’ll Own

Act as a trusted technical counterpart to client teams throughout the engagement, helping them make sound decisions and create lasting capability as you:

• Discover:Validate business opportunities against AI capabilities and constraints, and identify new opportunities enabled by the technology.

• Design:Own solution design and system architecture across agents, tools, data, evaluations, controls, human oversight, and deterministic boundaries.

• Build:Personally implement the system's critical agents, integrations, evaluation infrastructure, permissions, observability, controls, and feedback loops.

• Deliver:Lead the team and client from implementation through adoption, owning engineering quality and production readiness while establishing a clear delivery rhythm and engineering accountability across the project team.

• Compound:Package successful work as tools, datasets, evaluations, patterns, and engineering methods.

What We’re Looking For

A sustained record of exceptional technical leadership that generated real business impact, including experience leading small engineering teams.

• Experience designing, shipping, and operating production-grade AI systems, with practical judgment across architecture, context, tools, evaluation, observability, production controls, reliability, and cost.

• A demonstrated ability to keep pace with advances in AI, test what matters, and change working methods when new capabilities prove substantive, evidenced by advanced use of agentic AI in day-to-day work.

• Repeated ownership of difficult stakeholder environments and the judgment to connect technical decisions to business value, user needs, risk, and organizational change.

• Excellent communication skills across engineering, product, and business stakeholders.

• Strong coding skills and the ability to write and review production-grade code in languages such as Python, TypeScript/JavaScript, or similar.

• A strong engineering foundation and the first-principles judgment to understand what established practices protect and how those protections should be implemented in AI-native systems.

• Strong statistical and experimental judgment, including the ability to create the instrumentation, annotation, review, and feedback loops needed to learn from uncertain AI behaviour and improve systems over time.

Additional strengths

• Experience operating AI systems in security-sensitive or regulated environments.

• Experience creating AI tooling, evaluation infrastructure, data assets, or engineering platforms that serve multiple projects.

• A track record of hiring, onboarding, and developing engineering talent.

• Meaningful open-source work, public technical contributions, or active participation in the AI-engineering community