Engineering Manager (W/M)

Lesaffre is a global leader in yeasts and fermentation, crafting solutions for baking, food taste and pleasure, health care and biotechnology. The company traces its roots to northern France, where a family group started in 1853, and it has grown into a multinational with a truly international footprint. Today, Lesaffre employs about 11,700 people across more than 50 countries and reports a turnover of 3,2 billion euros.

In the Digital, Data & Tech division, transformation runs through delivery work, turning ideas into tangible products that customers rely on. Within that ecosystem, the delivery organization brings together Data, Software and Web engineering squads that build the core products the business uses every day. As the company scales its engineering, it is looking for an Engineering Manager who can raise the bar technically while growing the people who build the products, all while embracing AI-assisted and agentic engineering practices that are reshaping how teams operate.

The Engineering Manager role is a dual, hands-on leadership position. You’ll stay close to code and architecture, while also shaping team structure, developing engineers, and allocating talent to meet the group’s priorities. The role is based onsite in Marcq-en-Barœul, France, and fluency in English and French is required for local and global collaboration.

Guiding engineering craftsmanship and culture at Lesaffre

In this position you act as both a technical mentor and a people leader, driving not only the quality of what is shipped but also the growth of engineers across the Solution Engineering squads, data, software and web. You’ll be responsible for staffing and allocation decisions that balance delivery commitments with individual development as priorities shift, and you’ll cultivate a “One Team” culture that puts software craftsmanship, ownership, automation-first thinking and continuous learning at the center.

You’ll lead hiring end to end with HR, shaping role profiles, building pipelines and running interview loops. On the technical side, you’ll stay close to the code and design decisions, establishing engineering best practices, coding standards, testing and CI/CD, observability and documentation. You’ll help define reusable patterns and “Golden Paths” with the Lead Cloud & Solution Architect and the Platform Engineering Manager, making the right approach the easiest one for the teams. You’ll also track engineering health through metrics like deployment frequency, lead time, change failure rate and MTTR, using those signals to drive improvements rather than surveillance.

Agentic engineering, the AI-augmented development world, gets a clear seat at the table. You’ll guide the adoption of AI coding assistants, agent-driven automation, code generation, automated reviews and test generation to lift quality and velocity, while shaping how these new practices impact team structure and staffing. Governance matters here: you’ll set guardrails for security, IP protection, data confidentiality and human-in-the-loop review of AI-produced code, and you’ll provide tooling and playbooks to keep the team productive. Finally, you’ll own delivery reliability and run the FinOps mindset, balancing new features with technical debt reduction and building cost awareness into sizing of Cloud and Data resources.

What the team needs from you

Must-have skills & experience

• More than a decade of experience in software, cloud or data engineering, with a proven track record of both hands-on technical leadership and people management in roles like Tech Lead, Tech Lead Manager or Engineering Manager
• A strong technical foundation across cloud platforms (AWS and/or Azure) and modern DevOps practices, with credibility as an engineer, tech lead or architect
• Direct experience with modern data ecosystems (Snowflake or an equivalent platform), including pipelines, data modeling and governance
• A credible point of view on AI-assisted and agentic engineering and an understanding of how these practices reshape team organization
• Proven Agile leadership in a product-driven environment, using methods such as Scrum or Kanban
• A solid culture of software quality, including clean code, test-driven development, code reviews, observability and FinOps-minded delivery
• Excellent communication skills that bridge deep technical work with business stakeholders
• Fluent in English and French, both written and spoken, for local collaboration and global documentation

Nice-to-have skills

• Experience introducing AI coding assistants or agent-based workflows in a production engineering team
• Hands-on background as a Software Engineer, Data Engineer or DevOps/SRE
• Exposure to product-oriented operating models such as You build it, you run it, or Team Topologies
• Understanding of secure-by-design principles and applicative FinOps

Pay, benefits and practical details

The role is onsite in Marcq-en-Barœul, France, and requires fluency in both English and French for local collaboration and global documentation.

Lesaffre presents itself as a successful family-owned company with a long history where people matter, and it emphasizes a mission to nourish and protect the planet. The company offers the chance to work in a real international environment, with a culture that values diverse backgrounds and perspectives. All of its jobs are open to people with disabilities.

Tips for applying to this role

Lead with concrete examples of how you’ve grown engineering teams, including clear career paths, upskilling plans and a structured performance process that you implemented.

Show practical evidence of your hands-on credibility in cloud and data environments, highlighting Snowflake or equivalent platforms, data pipelines and governance in real projects.

Be ready to discuss your approach to AI-assisted and agentic engineering, including guardrails, governance and how you rolled out tooling, playbooks and training to boost delivery quality and velocity.

Ask a precise question about how the company plans to measure engineering effectiveness in an agentic setup and how such tooling might influence team structure, staffing decisions and investment cases.