Teams at Bits In Glass

Own enterprise client relationships, product scope, AI requirements, acceptance criteria, outcomes, and weekly release cadence. Lead discovery, backlog prioritization, stakeholder alignment, domain expert coordination, delivery health reporting, change adoption, and commercial risk management. The role requires shipping software in regulated industries, understanding LLM capabilities, managing fixed-fee engagements, and communicating with executive stakeholders.

Lead AI architecture across multiple client engagements, shaping solutions during pre-sales and governing designs through delivery. Define model hosting, security, data residency, integration, evaluation, observability, and cost standards. Maintain reference architectures and reusable accelerators, review code and designs, prototype solutions, mentor AI and data engineers, support technical hiring, and represent the company before enterprise architecture and security boards. The role requires hands-on enterprise software and production LLM experience, commercial judgment, and willingness to travel to Canadian client sites.