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About the role
- Senior AI architect shaping enterprise LLM engagements for Bits In Glass and ConveneAI. Governing architecture, building reusable standards, and mentoring delivery teams.
Responsibilities
- Shape client engagements during the sales cycle by assessing technical feasibility and realistic 8–12-week production scope
- Push back on requirements that cannot be delivered before contractual commitments
- 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 decisions involving data residency, inference hosting, identity and access, network isolation, and systems-of-record integration
- Unblock pods through pairing and review
- Own technical escalations and provide candid status assessments to the Product Owner and leadership
- 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 models, frameworks, and tooling for inclusion in the standard stack
- Build reusable technical assets that improve pod delivery efficiency
- 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
- Read code, prototype solutions, and defend designs before bank and insurer architecture review boards
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 AI-system failure modes
- Enterprise architecture fluency covering 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 undeliverable deals and hold that position under commercial pressure
- Legally entitled to work in Canada
- Willing to travel to client sites
- Bonus: architecture leadership at a consultancy or systems integrator, or Field CTO/principal architect experience at an AI, data, or cloud platform vendor
- Bonus: regulated-industry experience with systems such as Guidewire, Duck Creek, core banking, or clinical systems
- Bonus: self-hosted or open-weight model deployment, fine-tuning, distillation, and private inference architecture
- Bonus: experience building reusable reference architectures or accelerator libraries
- Bonus: experience scaling a delivery organisation
- Bonus: published writing, conference talks, or open-source work on applied AI architecture
Benefits
- Meaningful equity at the stage where technical decisions determine whether the delivery model scales or stalls
- Initial employment on Bits In Glass payroll with intended transition to a permanent position directly with Convene AI after approximately 12–18 months, subject to business requirements and transition arrangements
- Collaboration with the support, culture, and established consulting expertise of Bits In Glass
- Direct working relationship with the founders and senior AI operators
- Genuine breadth across pre-sales shaping through production operations and multiple industries
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Degree requirement
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