Senior Solution Architect – AI, Technical Lead

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

📋 Description

• Participate in discussions with clients during sales cycles to evaluate technical feasibility and define production deliverables for 8- to 12-week projects.

• Challenge requirements that cannot be fulfilled prior to contractual commitments.

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

• Draft technical components of proposals and statements of work.

• Assist in defining measurable and defensible outcome metrics.

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

• Conduct architecture reviews at project kickoff and established checkpoints for each live engagement.

• Manage data residency, private versus hosted inference, identity and access controls, network isolation, and integration strategies.

• Facilitate the unblocking of pods through pairing and review processes.

• Handle technical escalations when projects veer off course.

• Monitor inference costs, latency, and reliability across projects.

• Maintain the ConveneAI reference architecture and accelerator library.

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

• Assess new models, frameworks, and tools for integration into the standard stack.

• Create reusable technical assets that enhance pod delivery capacity.

• Mentor GenAI Engineers and Data Engineers during design and code reviews.

• Conduct interviews and assess technical hires while helping to shape the engineering career pathway.

• Collaborate with senior AI architects globally to ensure consistent standards are upheld.

⛳️ Requirements

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

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

• Proven track record as the technical owner across multiple concurrent client projects.

• In-depth 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 failure modes.

• Strong understanding of enterprise architecture, including identity and access management, security posture, data residency, network isolation, and model hosting alternatives.

• Experience obtaining approval from a regulated client's review board for design proposals.

• Commercial awareness, particularly how architectural choices impact gross margins on fixed-fee projects.

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

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

• Legally authorized to work in Canada.

• Willingness to travel to client locations.

🏝️ Benefits

• Significant equity at a stage where technical decisions influence whether the delivery model scales or falters.

• Collaboration with founders and senior AI professionals.

• Supportive culture and established consulting expertise from Bits In Glass.

• Opportunity to engage in cutting-edge AI solutions and contribute to a burgeoning AI organization.