Senior Solution Architect - AI, Technical Lead

Job Description:

• 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

Requirements:

• 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

Benefits:

• 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