Forward Deployed Engineer Lead

About the Role

Formel AI combines generative AI with formal methods to pioneer reliable, transparent, and cost‑efficient large language models.

As our Forward Deployed Engineer Lead , you will be at the intersection of cutting‑edge AI research and real‑world applications. You’ll work directly with design partners and early customers to valorize Formel AI’s technology—combining large language models with formal methods. This is a hands‑on technical leadership role where you’ll own the end‑to‑end technical relationship with our most strategic partners, translate customer needs into product requirements, define success criteria, integrate our solutions into their environments, and prove the value of formally verified AI in production settings.

Key Responsibilities

• Lead technical partnerships: Own the technical relationship with 2‑3 design partners, understanding their requirements, constraints, and success metrics
• Deploy and integrate: Implement Formel AI’s solutions in customer environments, including API integrations, workflow customization, and infrastructure setup
• Bridge product and customers: Translate customer feedback into product requirements and work closely with the development team to shape the roadmap
• Prove value through PoCs: Design, scope, and execute proof‑of‑concept projects that demonstrate measurable impact and build conviction for full deployment
• Build reusable patterns: Create documentation, integration templates, and best practices that scale our deployment approach
• Build the function: Define the playbook and eventually build a team as we scale

What we are looking for

Essential Qualities

• Customer‑first mindset: Energized by understanding customer problems and focused on delivering real value
• Hands‑on technical excellence: Able to ship production‑grade code and integrations autonomously in evolving environments
• Comfort with deep tech: Able to learn complex technical concepts and explain them clearly to non‑experts
• Ownership and autonomy: Take end‑to‑end ownership of outcomes and thrive with minimal supervision
• Excellent communication: Communicate technical concepts clearly to both technical and business stakeholders in French and English
• Startup adaptability: Comfortable with rapid iteration, changing priorities, and wearing multiple hats

Background

• 5+ years of software engineering experience with strong fundamentals in Python, APIs, and cloud infrastructure
• Proven experience deploying complex technical solutions in customer environments (consulting, solutions engineering, or technical account management)
• Track record of working with enterprise or technical customers in high‑stakes domains (healthcare, finance, legal, etc.)

Required Skills

• Python Full‑stack Expertise
  • Proficiency in a python‑based backend framework (FastAPI, Flask, Django, etc.)
  • Strong foundations in SQL, NoSQL, and data modeling
  • Core skills in cloud computing and server management (AWS/GCP/Azure CLI, Bash, Docker, Kubernetes)
  • Hands‑on experience with a prototyping framework like Streamlit, Gradio, Dash, or similar
• Product‑Led Tools & Methodologies
  • Experience with product tools (Linear, Jira, Notion, etc.)
  • Track record in complex product KPI establishment
• LLM & AI Infrastructure
  • Experience deploying and integrating LLM APIs (OpenAI, Anthropic, etc.)
  • Fundamentals of prompt engineering and RAG architectures
  • Familiarity with an LLM orchestration tool

Benefits

• Financial & perks
  • Competitive cash salary and equity (BSPCE) in a high‑potential company
  • Health insurance (Alan) for you and your family (partner and kids)
  • Daily lunch vouchers (Swile)
  • Hybrid work model with a strong emphasis on in‑office collaboration (typically 3‑4 days per week at the office) to foster team cohesion, spontaneous discussions, and deep work together

What makes this role unique

• Founding team impact: Join as one of the first employees and shape the trajectory of a moonshot deep‑tech company
• Mission‑driven startup: Help solve the key pressing challenges of AI—ensuring LLMs are trustworthy, transparent, and cost‑effective, with direct benefits for environmental sustainability
• Work with cutting‑edge technology: Build systems that combine LLMs with formal verification—an emerging field at the forefront of AI safety and reliability where breakthrough developments happen every week
• World‑class team: Collaborate with a scientific advisory board from leading institutions (Ecole polytechnique, ENS Paris‑Saclay, etc.) and experienced business angels from top tech companies (Datadog, Dataiku, Nabla, Artefact, and more)
• Strategic customers: Work with leading companies in healthcare, enterprise software, and other mission‑critical domains
• Flexibility of an early‑stage startup: Autonomy to define how you work and what you prioritize

Hiring Process

• Apply and submit your resume using a Google Form
• Initial screening call (30 min): Get to know each other, discuss your background and our mission
• Technical deep‑dive (60 min): Walk through past deployment projects, technical decisions, and problem‑solving approach
• Case study (take‑home + 60 min discussion): Design a full project development plan for a realistic customer scenario
• Founder interview (60 min): Meet the founding team to discuss vision, culture, and how you’d shape this role