Job Description
About MyBlueprint
myBlueprint is a leading developer of K-12 EdTech tools used by over 1 million students across Canada. We create best‑in‑class digital portfolios and career/life planning tools to support student success and documentation of learning. You can learn more about us at www.myBlueprint.ca.
Our vision is to empower every student to thrive and succeed in education, career, and life. We’re creating an active and engaging learning environment for all students, and we’re excited about what's next. Come grow your career with us!
About The Opportunity
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.
This role is
not
a traditional AI Product Manager position focused on feature brainstorming or experimentation. This is a
highly technical product architecture role
responsible for designing the
AI foundation
that will power every future experience in our product: guidance, feedback, assessment support, personalization, and district‑aligned recommendations.
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 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.
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!
What You Will Own
The AI Foundation & Data Architecture
You will define the conceptual and structural blueprint for how AI understands student data across the platform, including:
Architecting the foundational learner data model
Defining relationships across student work, plans, goals, opportunities, assessments, and skills
Designing schemas, relationships, and metadata strategies
Determining which signals are precomputed vs. generated on‑demand
Your work becomes the backbone for all future AI‑driven features
Extraction & Retrieval System Design
You will specify how raw student content becomes structured intelligence. This includes defining:
The extraction pipeline (text, audio, image, and document signals)
Data tagging and enrichment strategies
The retrieval and indexing approach
How different sources of student information become queryable context for AI
You won’t implement the pipelines — but you will define their required behaviour with clarity and precision
RAG, Orchestration & Routing Architecture
You will outline the logic that determines:
How the platform retrieves relevant evidence and context
How tools and retrieval methods interact with the intelligence layer
When generative models are used — and when they are not
How AI experiences draw from a single shared foundation
This includes defining the guidance the engineer follows to build the system
Cost‑Aware AI Decisioning
You will design the strategy that keeps AI reliable and affordable. This includes:
Establishing an SLM‑first approach
Defining when LLMs are allowed to run
Setting cost envelopes and routing constraints
Identifying caching opportunities and efficiency guardrails
You ensure we can scale AI across millions of students, sustainably
Vertical Slice Scoping & Delivery
You will scope and deliver the first end‑to‑end AI experiences that demonstrate platform value. This includes early vertical slices such as:
AI‑powered insights from student work
Early guidance and reflection experiences
Initial educator‑facing AI workflows
You define the slice, requirements, evaluation criteria, and technical expectations — and your engineering partner builds it. Experience translating system design into product decisions and user‑facing impact is essential
Innovation Pod Leadership
You are expected to join our team first, forming the initial half of a two‑person innovation team. Shortly after you begin in this technical product role, we will also hire a dedicated AI‑focused engineer, and the two of you will collaborate daily to move quickly, test ideas, and deliver early vertical slices that evolve into core platform features. This will include:
Setting priorities and defining the 90‑day architectural plan
Delivering prototypes, demos, and early pilots
Ensuring outputs integrate into the main product safely and cleanly
Collaborating closely with the Director of Engineering and Director of Product to ensure feasibility, alignment, and delivery; maintaining alignment with technical teams while operating autonomously
What You Will Have
Technical Product Strength
Experience defining or architecting AI systems (RAG, embeddings, routing, data models)
Ability to translate system design into product decisions and user‑facing impact
Ability to write clear pseudo‑APIs, data contracts, JSON/proto definitions
Comfort defining SLM‑first pipelines and LLM escalation rules
Deep Systems Understanding
Understands platforms, not isolated features
Experience connecting multiple data sources into a unified conceptual model
Ability to design structured signals and retrieval patterns
AI Architecture Fluency
Familiarity with embeddings, vector DBs, RAG patterns, multimodal pipelines
Ability to reason about token cost, latency, and reliability
Experience with hybrid (rules → SLM → LLM) systems
Product Leadership
Excellent communicator who can simplify ambiguous technical concepts
Ability to collaborate with engineers without taking on an engineering role
Proven ability to ship 0 → 1 systems
Comfort running independently with minimal oversight
Bonus Points For
Familiarity with EdTech or education‑related technology is highly preferred
Familiarity with OpenAI, Anthropic, Google models, and SLM families (Phi, Gemma, Llama 3.x)
Experience integrating district or tenant‑specific datasets (e.g., dual credit, apprenticeships)
Experience designing evaluation harnesses for LLM outputs
Experience with multi‑agent architectures or tool‑based orchestration
Experience integrating automation and workflow tools (e.g., n8n, Slack API, Productboard API, Salesforce API) to streamline product operations
Bachelor’s degree in Computer Science, Data Science, or a related field
Compensation
The salary range for this role is $110,000 – $140,000 CAD, with compensation determined based on the successful candidate’s experience and qualifications.
Our Team
Accountability : We take ownership of our work and responsibilities. You’ll manage a dynamic workload and may face occasional extra hours during peak periods. Our team thrives under pressure and holds itself accountable for delivering results and meeting high standards. You won’t be a good fit if you’re not comfortable with a demanding work environment and fluctuating workloads.
Collaboration : We enhance each other’s success through effective teamwork and shared goals. While most of our work is remote, we gather in the office 1‑2 times a month. These meetings foster strong relationships and productive collaboration. You won’t be a good fit if you prefer not to engage in occasional in‑person meetings or struggle with remote teamwork.
Growth : We’re dedicated to continuous improvement and professional development. You’ll encounter challenges that promote learning and growth. We offer skill‑building and career advancement opportunities. You won’t be a good fit if you’re not open to new challenges or actively seeking growth.
Adaptability : We operate fast and priorities shift rapidly. You’ll need to adapt to change and manage multiple tasks efficiently. You thrive here if you excel in a dynamic setting and embrace change. You won’t be a good fit if you struggle with varied responsibilities or shifting priorities.
Transparency : We prioritize clear, open communication. We’re upfront about our expectations and recognize this environment isn’t for everyone. Accurate, honest interactions are key. You won’t be a good fit if you’re uncomfortable with transparency and honest feedback.
Community : We work with people passionate about education and our mission. We’re committed to making a meaningful impact and seek those who share this dedication. You won’t be a good fit if you’re not passionate about our mission or share our commitment.
Benefits & Perks
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 on‑s...
