About the role

Solution Architect leading enterprise AI architecture, governance, and delivery standards for Bits In Glass and ConveneAI. Shaping client engagements and scaling reusable AI accelerators.

Responsibilities

Join client conversations during sales cycles to assess technical feasibility and scope production deliverables for 8- to 12-week engagements
Challenge requirements that cannot be delivered before contractual commitments are made
Own architecture decisions covering model selection, build versus buy, accelerator reuse, bespoke work, and hosting approach
Write technical sections of proposals and statements of work
Help define measurable and defensible outcome metrics
Represent ConveneAI in client architecture, security, and vendor review boards
Run architecture reviews at kickoff and defined gates for every live engagement
Govern data residency, private versus hosted inference, identity and access, network isolation, and integration patterns
Unblock pods through pairing and review
Own technical escalation when engagements drift off track
Monitor inference cost, latency, and reliability across engagements
Own the ConveneAI reference architecture and accelerator library
Set standards for agent design, evaluation, observability, security, and cost management
Evaluate new models, frameworks, and tooling for inclusion in the standard stack
Build reusable technical assets that improve pod delivery capacity
Mentor GenAI Engineers and Data Engineers through design and code review
Interview and calibrate technical hires and help define the engineering career path
Collaborate with senior AI architects across the global operating bench to maintain consistent standards

10 or more years building and shipping enterprise software
At least 2 years on production LLM or agentic systems that real users depended on
Track record as the technical owner across multiple concurrent client engagements
Deep hands-on capability with Python, cloud architecture (AWS, Azure, or GCP), distributed systems, and API and integration design
Production experience with agent architectures, retrieval at enterprise scale, evaluation, cost per task, latency, observability, and failure modes
Enterprise architecture fluency in identity and access, security posture, data residency, network isolation, and model hosting options
Experience getting a regulated client's review board to approve a design
Commercial literacy, including understanding how architecture decisions affect gross margin on fixed-fee engagements
Credibility with client CIOs or Chief Architects and hands-on engineers
Judgement to recommend against an undeliverable deal and maintain that position under commercial pressure
Legally entitled to work in Canada
Willing to travel to client sites

Meaningful equity at the stage where technical decisions determine whether the delivery model scales or stalls
Collaboration with founders and senior AI operators
Support, culture, and established consulting expertise of Bits In Glass
Opportunity to work on innovative AI solutions and contribute to an emerging AI organization