SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
Mistral is building a Head of FDE Learning Programs role to architect and scale the learning system for its Field Deployment Engineering (FDE) organization. The company is expanding from initial hires to several hundred Deployment Strategists and Applied AI Engineers within two years, and this role owns ensuring capability growth matches headcount without compromising quality standards.
You will own the complete learning ecosystem: designing practical learning content across technical skills, strategic and business capabilities, and product enablement; building a structured onboarding path from first week to independent customer work; creating and operating technical bootcamps that translate new products and research into field-ready training; designing strategic bootcamps to empower client-facing teams in business and partnership discussions; and establishing readiness standards that ensure consistent quality across all regions.
Key responsibilities include owning the full program roadmap, curriculum design, instructor network development, regional delivery, measurement frameworks, and the central team structure. You will launch programs immediately while building the scalable operating model needed to serve hundreds of FDEs without reducing content to generic training. Cross-functional collaboration is essential—you'll work closely with functional managers, Product, Engineering, Science, People, GTM Enablement, DevRel, and regional leaders. You'll also establish knowledge management systems to keep internal resources current and ensure stakeholders have access to the latest material and customer insights.
Mistral's culture emphasizes shipping results over process, direct feedback, low ego, and high standards. The organization operates with minimal bureaucracy, and the best ideas win regardless of hierarchy. You'll work across distributed teams spanning Europe, North America, Asia, and the Middle East.
REQUIREMENTS:
Must-have experience:
- Built a learning, enablement, or capability function for a technical organization during rapid growth
- Ability to start as the first dedicated owner, deliver useful programs immediately, and build the team and operating model for several hundred people
- Technical fluency sufficient to work credibly with AI engineers, Product, and Science teams; inspect program substance; and challenge unclear or outdated material
- Designed programs that work across cohorts, regions, and experience levels without reducing content to generic training
- Can lead work across senior stakeholders, subject-matter experts, managers, and operational partners without relying on reporting lines
- Make firm trade-offs when hiring demand, expert capacity, and program quality compete
- Attention to full learner experience: communications, scheduling, practice, feedback, and manager follow-through
- Use evidence to decide which programs to expand, revise, or stop
- Clear communication with executives, managers, technical experts, and learners
- Fluent in English and able to work across regions and time zones
Ideal-to-have experience:
- Scaled a one-person or small learning function into a team serving hundreds of technical employees
- Built onboarding that kept pace with rapid hiring in engineering, FDE, solutions, consulting, or professional-services organizations
- Designed and operated technical bootcamps or cohort-based learning programs
- Technical DevRel, developer education, or related roles built around demos, code examples, workshops, and practitioner communities
- Built role- and level-based curricula connected to skills frameworks or career progression
- Managed global programs with contributors and learners across multiple regions
- Worked closely with Product, Engineering, Science, People, and customer-facing teams
- Designed practical assessments, readiness standards, or certifications
- Experience with learning platforms, knowledge systems, AI coaches, or program-operations tooling
- Background in AI/ML or other technically complex, fast-changing fields
