Jobs at Board of Innovation

Design, implement, and ship production-grade AI systems: multi-step agents, retrieval pipelines, and service wrappers. Own evaluation, observability, testing, CI/CD, and operational tradeoffs. Collaborate with engineers, strategists, and designers and participate in client scoping through delivery.

Design and build responsive front-ends, scalable back-end services, and database/pipeline integrations that connect AI models to users. Own architecture, implementation, testing, deployment, observability, and performance. Integrate models, agents, and retrieval systems with client-facing applications and collaborate with designers, AI engineers, and strategists from scoping through delivery.

Lead end-to-end AI transformation engagements: define strategy, scope use cases, build and deploy AI products to production, drive adoption and measurable value, grow accounts via proposals, and coach teams while championing AI-first practices.

Lead end-to-end delivery of complex AI transformation programs: structure opportunities, build business cases and roadmaps, design operating models, drive change, engage C-suite, and develop reusable AI IP while coaching teams.

Lead end-to-end AI transformation engagements for enterprise clients: structure opportunities, build business cases and roadmaps, design operating models, drive change, mentor teams, and contribute to proposals and commercial growth while building practical AI workflows and tools.

Lead AI strategy and engineering engagements, identify growth opportunities, design solutions, and manage client relationships effectively.

The Full-Stack Engineer will build AI-integrated products, handling front-end and back-end development, as well as testing and deployment processes, while collaborating with others on technical solutions in a consulting environment.

Lead AI transformation engagements focusing on strategy, delivery, and client outcomes while managing proposals and team coordination.

As an AI Engineer, you'll design and build AI systems for production applications, focusing on client solutions and maintaining system performance through evaluations and observability.