Heart & Stroke is dedicated to promoting health and enhancing recovery. The Technical Product Engineer will support the design and rapid prototyping of AI and data integration initiatives, serving as a bridge between business needs and engineering delivery while contributing to solution design and development.
Responsibilities:
- Work closely with business stakeholders, Product Managers (including AI Enablement Product Manager), and Project Managers to understand business problems, workflows, and desired outcomes
- Help translate business requirements into clear technical requirements, assumptions, and solution concepts
- Work with AI consulting vendors
- Engage technology engineering stakeholders across applications, platforms, data and cloud infrastructure as required
- Communicate technical ideas, options, and constraints in a clear and accessible way to non-technical stakeholders
- Support collaborative working sessions to shape use cases and define prototype scope
- Analyze business needs and identify feasible technical approaches, including AI, automation, data integration, and application-based solutions
- Help determine when solutions are best addressed via configuration, low-code/no-code tools, or custom engineering
- Identify data inputs, integration points, and system dependencies required to support proposed solutions
- Document technical assumptions, constraints, and options to inform decision-making and prioritization
- Design and build lightweight prototypes, proof-of-concepts, and technical experiments to validate solution feasibility
- Develop small-scale integrations (e.g., API-based connections, data ingestion pipelines) where appropriate
- Leverage modern development frameworks and AI tooling to rapidly test and iterate on ideas
- Produce working demonstrations and artifacts to support business and technology decision-making
- Engage appropriate engineering, data, security, and infrastructure SMEs to assess production considerations early in the lifecycle
- Help identify non-functional requirements including performance, scalability, security, and maintainability
- Support the transition of validated prototypes into formal engineering delivery, including documentation of design, dependencies, and risks
- Contribute to solution design discussions under the guidance of senior technical leaders, using modern frameworks and engineering best practices
- Ensure code quality through standards, peer reviews, automated testing, and CI/CD pipelines
- Embed security and compliance into development workflows
- Partner with Director to advance engineering standards and operating model
- Drive automation, CI/CD robustness, observability, and documentation maturity
- Plan and execute a structural technical debt reduction exercise
- Contribute to internal application solution design standards, integration standards, API governance, and patterns (REST, event‑driven, messaging)
- Contribute to selected full-stack development and data integration and transformation work where scope is well-defined and supported by senior engineers
- Support development of front-end, backend, and integration components using modern frameworks and tools
- Assist in troubleshooting, testing, and improving solutions during pilot and early delivery phases
- Responsibly leverage AI tools such as Github Co-pilot to accelerate development and enhance quality
- Build knowledge of Heart & Stroke enterprise systems, data structures, and integration patterns
- Stay current with emerging AI tools, development frameworks, and prototyping approaches
- Develop skills in technical product thinking, solution design, and stakeholder collaboration
- Seek feedback and coaching to progressively take on more complex technical shaping responsibilities
- Support disaster recovery and high-availability strategies
Requirements:
- 0 - 2 years of relevant experience (including internships, co-op, or project-based experience) in software development, data integration, or AI-enabled applications
- Demonstrated experience contributing to full-stack application development, including front-end and backend components
- Experience working with APIs, external data sources, or asynchronous data processing workflows
- Exposure to cloud-based development environments (e.g., AWS, Azure, or GCP)
- Experience building prototypes, proof-of-concepts, or experimental solutions to solve real-world problems
- Experience with user-centered design practices
- Bachelor's degree in Computer Science, Software Engineering, Computer Engineering, or a related technical discipline
- Demonstrated academic focus or coursework in software development, data systems, and artificial intelligence
- Strong foundational programming skills in modern languages such as Python, JavaScript, or TypeScript
- Experience with full-stack application development, including front-end interfaces, backend services, and API integration
- Familiarity with data integration concepts, including working with external data sources, structured/unstructured data, and asynchronous processing workflows
- Exposure to AI-enabled application development, including prototyping with LLMs, automation tools, or machine learning-based solutions
- Understanding of modern development practices such as version control, testing, CI/CD, and deployment workflows
- Familiarity with cloud-based development environments and services
- Ability to translate business needs into technical approaches, prototypes, and solution options with guidance from senior team members
- Strong analytical, problem-solving, and troubleshooting skills
- Strong written and verbal communication skills, including the ability to explain technical concepts to non-technical stakeholders
- Curiosity, adaptability, and a strong learning orientation in a fast-evolving technology environment
- Ability to work collaboratively across product, engineering, data, and business teams
- Experience developing or experimenting with AI/ML or LLM-based solutions (e.g., integrating models into applications, working with structured/unstructured data)
- Participation in hackathons, innovation challenges, or technical competitions that examine both business and technology implications and outcomes
- Experience working on user-facing applications with performance or usability considerations
- Exposure to CI/CD pipelines, deployment workflows, or DevOps practices
- Experience working on projects with multiple developers using shared codebase and multiple external integrations
- Combined exposure to both technical (software/engineering) and business or product-oriented coursework or internship experience
- Participation in applied research, capstone projects, or technical competitions related to software and AI
- Experience with frameworks and tools such as React, Next.js, Node.js, Flask, or FastAPI
- Exposure to AI/ML tooling, prompt engineering, model integration, or multimodal AI use cases
- Experience working with APIs, dashboards, or user-facing applications
- Exposure to AWS, Azure, or GCP