Lead AI Engineering Development
The ideal candidate for this role will be a seasoned software engineer with experience in developing enterprise-grade AI tools and systems. You will have a strong background in AI/ML, back-end, and/or full-stack development, including API design, cloud services, and modern frameworks.
About the Role
You will be responsible for leading the design of our engineering practice, hiring and managing our engineers across all disciplines, and establishing the infrastructure, environments, and operations needed to consistently ship high-quality AI applications.
This is a player-coach role where you will architect systems, set up infrastructure, and write code - but also shape our technical strategy, lead hiring, and grow our team.
You will work closely with our strategists to turn client opportunities into scalable, robust technical solutions.
Key Responsibilities
* Define and own the technical architecture for our AI applications, including ML, front-end, back-end, and data infrastructure.
* Set up best practices for version control, code review, testing, and documentation.
* Establish local, staging, and production environments, as well as CI/CD pipelines.
* Build our technical stack with long-term scalability, maintainability, and security in mind.
Requirements
* Bachelor's or Master's degree in Computer Science (or related field).
* 10+ years of experience in software engineering, including 2+ years in a technical leadership role.
* Deep experience developing enterprise-grade AI tools, systems, or capabilities for large companies.
* Experience in a consulting/agency/studio/client delivery environment.
What We're Looking For
* Expertise in AI/ML/back-end and/or full-stack development, including API design, cloud services, and modern frameworks.
* Hands-on experience with Python-based AI applications, especially integrating LLMs via APIs.
* Expertise AI application tooling like LangChain, vector databases, or RAG workflows.
* Strong understanding of DevOps fundamentals, such as Docker, CI/CD, and cloud deployments.
* Comfortable balancing speed and quality, with a bias for action and iteration.