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Salary: USD 150,000 - 250,000 / annual
Distyl AI is an applied AI technology company partnering with major institutions to rearchitect critical operations using frontier AI. The company works with the largest companies in telecom, healthcare, insurance, manufacturing, consumer goods, and global social organizations, deploying AI-native systems that affect hundreds of millions of consumer interactions, tens of millions of supply chain transactions, and millions of patient journeys.
As an AI Engineer, you will build and operate production AI systems that deliver measurable business value in customer environments. This is a hands-on role for engineers who thrive in ambiguous problem spaces and take ownership of outcomes. You will design, implement, deploy, and iterate on end-to-end AI systems in close partnership with customers, subject matter experts, and other Distyl engineers.
Key responsibilities include:
- Building and operating AI systems deployed in customer environments, owning system behavior, reliability, and production usefulness
- Designing and implementing compound AI workflows combining models, prompts, agents, tools, retrieval, evaluation, feedback loops, and execution into coherent production systems
- Developing clean, maintainable Python services and application logic that integrate AI capabilities into customer workflows, data platforms, APIs, and existing applications
- Operating on live systems by measuring behavior, identifying failure modes, debugging issues, and iterating rapidly to improve quality and reliability
- Building evaluation frameworks, test cases, feedback mechanisms, and observability patterns to understand and improve AI system performance
- Working directly with customer stakeholders and subject matter experts to understand workflows, clarify requirements, and adapt systems as needs evolve
- Using AI-native engineering tools to accelerate implementation, debugging, experimentation, and system improvement
- Collaborating with other AI Engineers and team members to make pragmatic system design decisions balancing speed, robustness, maintainability, and customer impact
- Taking accountability for production outcomes of components, workflows, and systems you build
This is not a demo-building role. You are expected to make AI systems work in practice with real users, data, constraints, and accountability for production outcomes.
The role follows a hybrid collaboration model with 3+ days per week (Tuesday–Thursday) in the New York office. Travel is typically 10–30% depending on the project and customer needs.
REQUIREMENTS:
- 5+ years of software engineering experience
- Fluent in French (written and spoken) with the ability to lead technical discussions and collaborate directly with French-speaking clients
- Ownership mentality for AI systems; you take responsibility for whether systems deliver intended value in production and are comfortable making technical decisions and owning results
- Experience building AI systems; you have built applications powered by LLMs or other AI models and are comfortable composing multiple components into end-to-end systems, reasoning about system behavior holistically
- Strong engineering fundamentals; you write clean, maintainable Python and are comfortable building production software systems, understanding versioning, debugging, testing, performance, code review, and production readiness
- AI-native working style; you use AI tools daily to write and debug code, explore designs, analyze data, and automate work; you are curious about new model capabilities and actively incorporate them into your work
- Comfort in customer environments; you can work directly with customer teams, ask good questions, adapt quickly to new domains, communicate clearly about system behavior and limitations, and operate effectively in high-trust situations
- Pragmatic delivery mindset; you can navigate ambiguity, make progress with incomplete information, and balance speed with robustness
- Willingness to travel (10–30% depending on project and customer needs)
