Senior Solution Architect – AI, Technical Lead

This is a fully remote position, open to applicants in Canada.

📋 Description

• Influence client engagements throughout the sales process by evaluating technical feasibility and establishing a realistic 8–12-week production timeline.

• Challenge requirements that cannot be fulfilled before contractual obligations.

• Take ownership of architectural decisions related to model selection, build versus buy options, accelerator reuse, custom development, and hosting strategies.

• Compose the technical components of proposals and statements of work.

• Assist in defining measurable and justifiable outcome metrics.

• Represent ConveneAI in client architecture, security, and vendor review committees.

• Facilitate architecture reviews at project kickoff and at established checkpoints for every active engagement.

• Oversee decisions concerning data residency, inference hosting, identity and access management, network isolation, and systems-of-record integration.

• Remove obstacles for pods through collaborative pairing and review processes.

• Manage technical escalations and provide honest status updates to the Product Owner and leadership team.

• Track inference costs, latency, and reliability across various engagements.

• Maintain the ConveneAI reference architecture and accelerator library.

• Establish standards for agent design, evaluation, observability, security, and cost management.

• Assess models, frameworks, and tools for potential inclusion in the standard technology stack.

• Create reusable technical resources that enhance pod delivery efficiency.

• Mentor GenAI Engineers and Data Engineers through design and code evaluations.

• Conduct interviews and calibrate technical hires while helping to define the engineering career trajectory.

• Collaborate with senior AI architects across the global operational team to uphold consistent standards.

• Review code, prototype solutions, and defend designs before banking and insurance architecture review boards.

⛳️ Requirements

• A minimum of 10 years in building and delivering enterprise software.

• At least 2 years of experience with production LLM or agentic systems relied upon by real users.

• Proven track record as the technical lead across multiple simultaneous client engagements.

• Extensive hands-on experience with Python, cloud architecture (AWS, Azure, or GCP), distributed systems, and API and integration design.

• Practical experience with agent architectures, enterprise-scale retrieval, evaluation, cost per task, latency management, observability, and AI-system failure modes.

• Proficiency in enterprise architecture covering identity and access management, security posture, data residency, network isolation, and model hosting alternatives.

• Demonstrated experience obtaining approval from a regulated client's review board for a design.

• Commercial acumen, including an understanding of how architectural decisions impact gross margins on fixed-fee contracts.

• Established credibility with client CIOs, Chief Architects, and hands-on engineers.

• Sound judgment to advise against unfeasible deals and maintain that stance under commercial pressure.

• Legally authorized to work in Canada.

• Willingness to travel to client locations.

• Bonus: Leadership experience in architecture at a consultancy or systems integrator, or Field CTO/principal architect experience at an AI, data, or cloud platform vendor.

• Bonus: Experience in regulated industries with systems such as Guidewire, Duck Creek, core banking, or clinical systems.

• Bonus: Experience with self-hosted or open-weight model deployment, fine-tuning, distillation, and private inference architecture.

• Bonus: Experience in building reusable reference architectures or accelerator libraries.

• Bonus: Experience in scaling a delivery organization.

• Bonus: Published writings, conference presentations, or open-source contributions related to applied AI architecture.

🏝️ Benefits

• Meaningful equity at a stage where technical decisions will determine whether the delivery model can scale or will face challenges.

• Initial employment through Bits In Glass payroll with an intended transition to a permanent role directly with ConveneAI after approximately 12–18 months, subject to business needs and transition arrangements.

• Collaboration with the support, culture, and established consulting expertise of Bits In Glass.

• Direct engagement with the founders and senior AI professionals.

• A genuine opportunity to work across the pre-sales shaping process through production operations in multiple industries.