Engineering Manager (W/M)

Company Description

As a global key player in yeasts and fermentation, Lesaffre designs, manufactures and markets innovative solutions for Baking, Food taste & pleasure, Health care and Biotechnology.

Family group born in northern France in 1853, now a multi-national and a multicultural company, Lesaffre is committed to working with confidence to better nourish and protect the planet.

In close collaboration with its clients and partners, Lesaffre employs 11 700 people in more than 50 countries.

Lesaffre achieves a turnover of 3,2 billion euros.

Job Description

At Lesaffre, Digital, Data & Tech (DDTech) is a fundamental transformative force for Lesaffre growth. It is a lever to increase customer centricity and user experience, achieve operational excellence, supercharge R&D, and empower our teams across the entire company.

At the heart of this digital transformation is our delivery department, where we turn innovative ideas into impactful solutions. Central to that effort are our Solution Engineering squads, the Data Engineers, Software Engineers, and Web Engineers who build and ship the products our business relies on.

As our delivery scales, the way we engineer and the way we grow people must evolve together. We need a leader who can both raise the technical bar and grow the engineers, while embracing a new generation of AI-assisted and agentic engineering practices that are reshaping how software teams are structured and how they deliver.

In this context, Lesaffre is recruiting an Engineering Manager.

As the Engineering Manager, you wear two hats: you are a technical leader who stays close to the code, the architecture, and the quality of what we ship, and you are a people leader who grows engineers, shapes team structure, and allocates talent to the Group's priorities. You are fluent in modern agentic engineering practices (AI coding assistants, agent-driven workflows, automated review and testing) and you understand how they change the way engineering teams are organized, sized, and led. Technical credibility is essential: you cannot raise the bar or grow engineers without it.

Key Responsibilities: 

Team Leadership & People Management

• Grow the Engineers: Manage, mentor, and develop the engineers of the Solution Engineering squads (Data, Software, Web), building clear career paths, upskilling plans, and a fair, structured performance process.
• Staffing & Allocation: Own the dynamic staffing and allocation of engineers across the Product Squads, balancing delivery commitments, individual growth, and operational support as priorities shift.
• Culture Builder: Foster a "One Team" engineering culture grounded in software craftsmanship, ownership, automation-first thinking, and continuous learning.
• Hiring: Own the technical hiring process end to end with HR, defining role profiles, building the pipeline, and running interview loops.

Technical Leadership & Engineering Excellence

• Hands-On Credibility: Stay close to the code and the architecture. Contribute directly to design decisions and code reviews to guarantee secure, robust, and maintainable solutions.
• Define the Bar: Define, document, and champion engineering best practices, coding standards, code review, testing, CI/CD, observability, and documentation.
• Golden Paths: In partnership with the Lead Cloud & Solution Architect and the Platform Engineering Manager, promote reusable patterns and "Golden Paths" that make the right way the easy way.
• Engineering Health: Define and track engineering effectiveness metrics (e.g., DORA: deployment frequency, lead time, change failure rate, MTTR) and use them to drive improvement, not surveillance.

Agentic Engineering Practices

• AI-Augmented Development: Lead the adoption of AI-assisted and agentic engineering workflows, defining how the team uses AI coding assistants, agent-driven automation, code generation, automated review, and test generation to increase quality and velocity.
• Impact on Team Topology: Anticipate and shape how agentic practices change the way engineering teams are structured, sized, and staffed, and adapt squad organization and roles accordingly.
• Guardrails & Governance: Establish responsible-use guidelines for AI in engineering: security, IP protection, data confidentiality, dependency hygiene, and human-in-the-loop review of AI-generated code.
• Enablement & Evidence: Roll out the tooling and enablement (training, playbooks, prompt patterns) that make the team genuinely productive, and track the impact on quality, throughput, and developer experience.

Delivery, FinOps & Run Stability

• Reliable Delivery: Guarantee the resilience, maintainability, and quality of the applications the squads deliver, balancing new delivery with the deliberate reduction of technical debt.
• Applicative FinOps: Build cost awareness into engineering practices, sizing Cloud (AWS/Azure) and Data (Snowflake) resources to real usage and reducing waste through direct technical contribution.
• Reduce External Dependency: Strengthen internal engineering capability to reduce reliance on external providers where it makes sense.

Financial Management

• Engineering Cost Ownership: Contribute to the budget for your engineering resources, steering the internal-vs-external mix of your engineers to deliver against the roadmap cost-effectively.
• Engineering Cost & Value: Track the cost and value of the engineering work your teams produce, and feed applicative FinOps insights back into technical and staffing decisions.
• Investment Cases: Build and defend business cases for engineering investments, in particular agentic tooling, AI assistants, and upskilling, quantifying expected productivity and quality gains.

Performance Measurement & Reporting

• Engineering Metrics: Define and maintain engineering effectiveness metrics (DORA: deployment frequency, lead time, change failure rate, MTTR) alongside code quality and delivery indicators.
• Agentic Impact: Measure and report the impact of AI-assisted and agentic practices on throughput, quality, and developer experience.
• Leadership Reporting: Report progress, risks, and achievements to the Head of Engineering & Infrastructure through dashboards and regular reviews, translating technical results into business value.