AI Engineer (French Speaking)

Distyl AI•New York, NY

1d•$180,000 - $250,000•Hybrid

About The Position

Distyl AI is seeking a French-speaking AI Engineer to build and operate production AI systems that deliver business value in customer environments. The role involves translating operational needs into concrete system behavior and designing, implementing, deploying, and improving end-to-end AI systems in partnership with customers, subject matter experts, and other Distyl engineers. The systems must work reliably with real users, data, and enterprise constraints, rather than serving only as demonstrations. AI Engineers create compound AI workflows using models, prompts, agents, tools, retrieval, evaluation, feedback loops, and execution. They develop maintainable Python services and application logic that integrate AI into customer workflows and existing platforms, then measure system behavior, debug failures, and iterate based on evaluation and user feedback. The role also requires direct collaboration with French-speaking customers and a willingness to travel, typically 10–30% depending on project and customer needs. The position offers a base salary of $180,000–$250,000, depending on experience, location, and level, plus equity and a comprehensive benefits package. It follows a hybrid work model requiring at least three days per week, Tuesday through Thursday, in Distyl’s New York office. Distyl also has an office in San Francisco.

Requirements

At least 5 years of software engineering experience.
Fluency in spoken and written French, with the ability to lead technical discussions and collaborate directly with French-speaking clients.
Ownership mentality and willingness to take responsibility for whether AI systems deliver their intended value in production.
Experience building applications powered by LLMs or other AI models and composing components such as prompts, agents, tools, retrieval, evaluators, workflows, and integrations into end-to-end systems.
Ability to reason about AI system behavior holistically rather than treating models as black boxes.
Strong engineering fundamentals, including writing clean, maintainable Python and building production software systems.
Understanding of versioning, debugging, testing, performance, code review, and production readiness.
Daily use of AI tools to write and debug code, explore designs, analyze data, and automate repetitive work; curiosity about new model capabilities and techniques.
Ability to work directly with customer teams, ask effective questions, adapt to new domains, and communicate clearly about system behavior, limitations, and tradeoffs.
Effectiveness in high-trust, high-visibility customer situations.
Ability to navigate ambiguity, make progress with incomplete information, and balance speed with robustness for production systems.
Willingness to travel, typically 10–30% depending on project and customer needs.

Responsibilities

Build and operate AI systems deployed in customer environments, owning their behavior, reliability, and usefulness in production.
Design and implement compound AI workflows combining models, prompts, agents, tools, retrieval, evaluation, feedback loops, and execution to meet user and subject matter expert needs.
Develop clean, maintainable Python services and application logic integrating AI with customer workflows, data platforms, APIs, and existing applications.
Measure live system behavior, identify failure modes, debug issues, and iterate to improve quality, reliability, and user value.
Build evaluation frameworks, test cases, feedback mechanisms, and observability patterns to help teams understand and improve AI system performance.
Work directly with customer stakeholders and subject matter experts to understand workflows, clarify requirements, assess tradeoffs, and adapt systems as needs evolve.
Use AI-native engineering tools to accelerate implementation, debugging, experimentation, data analysis, and system improvement.
Collaborate with AI Engineers, AI Strategists, and other Distillers on pragmatic system design decisions balancing speed, robustness, maintainability, and customer impact.
Take accountability for production outcomes of the components, workflows, and systems built.
Travel as needed; travel is typically 10–30%, depending on the project, customer needs, and role on the engagement.

Benefits

Base salary range of $180,000–$250,000, depending on experience, location, and level.
Meaningful equity.
100% coverage of medical, dental, and vision insurance for employees and dependents.
Flexible time off.
Pre-tax HSA, FSA, and commuter accounts.
401(k).
Financial coaching resources.
Wellness benefits covering physical fitness and mental well-being.
Fertility and family-building benefits through Carrot.
Complimentary in-office lunches and snacks.
Access to state-of-the-art AI models and generous usage of modern AI tools.