Technical Product Manager, AI Systems & Architecture
About The Position
We are building the next generation of student success technology — powered by a unified intelligence layer that connects student work, learning pathways, and educator workflows across myBlueprint and SpacesEDU. We’re hiring a Technical Product Manager, AI Systems & Architecture, to define and operationalize the architectural backbone of our AI systems. This role is architect-first, feature-second. You will define the systems that allow AI to understand student work, interpret progress, and support educators — all from one shared platform layer. Your focus is on defining how the system behaves: the logic, flow, and structure that make the experience work. You will have support from Engineering to implement the underlying infrastructure. You’ll start as one half of a two-person team, initially on your own, with a dedicated AI-focused engineer to be hired shortly after you begin — allowing you to move quickly, think holistically, and deliver early vertical slices that evolve into core platform features. Success in this role is measured by: Clear, structured architectural decisions Crisp documentation and scoping Systems that are ready for engineering execution Vertical slices shipped with defined evaluation criteria This is not a “prompt ideation” or research-heavy strategy role. It is a systems design and delivery role. If you're energized by technical systems, data architecture, AI reasoning patterns, and designing the backbone of an AI-first product ecosystem, this is the role for you!
Requirements
- Crisp, structured communication
- Ability to define a realistic MVP scope (and clearly state what’s out of scope)
- Systems thinking across data, model, UX, and evaluation layers
- Comfort working at the intersection of product and architecture
- Hands-on technical experience with:
- Retrieval-augmented generation (RAG) pipelines
- Embeddings, vector databases, and hybrid retrieval
- Model routing and orchestration strategies
- AI evaluation approaches (human-in-the-loop, regression testing, signal tracking)
- Defining data contracts, schemas, pseudo-APIs, or structured JSON interfaces
- You don’t need to be an ML engineer — but you must think in architectural systems, not just features.
Nice To Haves
- Experience in any of the following areas is a plus:
- Education technology environments
- Evaluating and selecting foundation models (cost, latency, quality tradeoffs)
- Designing LLM evaluation systems (regression datasets, scoring rubrics, human review, monitoring)
- Building orchestration layers (multi-agent systems, tool calling, routing logic, fallback strategies)
- Working in multi-tenant or privacy-sensitive environments
- Integrating district- or tenant-specific datasets into AI workflows
- Automation and API integrations (e.g., n8n, Slack, Salesforce, Productboard)
Responsibilities
- AI Platform Architecture
- Extraction & Retrieval System Design
- Orchestration & Model Routing
- Cost, Reliability & Guardrails
- Vertical Slice Delivery
- Innovation Pod Leadership
Benefits
- Health and dental coverage
- Wellness spending account
- Flexible vacation days, with more earned annually
- Extra paid time off during holidays (Christmas to New Years) and quarterly wellness days
- One paid volunteer day per year to give back to a cause you’re passionate about
- $1,000 CAD annual learning and development fund
- Remote-friendly work environment with monthly In Office days for collaboration
- Work from anywhere for up to 2 months a year
- Regular team events and outings
- A results-oriented culture that rewards your efforts and fosters continuous learning and growth
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
No Education Listed
