Senior Solution Architect – AI, Technical Lead
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Job Description
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
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
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