Are you a hands-on engineering leader who enjoys building platforms from the ground up, solving ambiguous technical problems, and shipping quickly?

We’re looking for a Staff/Principal Software Engineer to help design and build a greenfield platform at the intersection of edge computing, distributed backend services, identity/trust signals, and AI/ML inference.

This is a high-impact individual contributor role where you will influence architecture, make critical technology decisions, and remain deeply involved in writing production code.

What You’ll Work On

- Design the end-to-end signal flow from CDN and edge detection through ingestion, processing, storage, and downstream routing
- Architect edge-layer solutions using edge workers, CDN functions, Lambda@Edge, or similar technologies
- Build scalable backend services and APIs using Java and Spring Boot
- Develop signal validation, normalization, persistence, and deterministic ingestion pipelines
- Integrate with identity, trust, and third-party signal providers using technologies such as JWT, JWS, PKI, OAuth 2.0, and public-key caching
- Build data-access layers, feature pipelines, and model-registry integration points for ML inference
- Make architectural decisions around AWS infrastructure, storage, reliability, observability, networking, IAM, and governance
- Collaborate closely with data science, product, and external partner teams

What We’re Looking For

- 8+ years of experience building production-grade distributed systems




- Deep hands-on expertise in Java, Spring Boot, API design, microservices, and event-driven architecture
- Strong experience with AWS cloud services
- Experience building systems that support ML inference, feature pipelines, model serving, feature stores, or data normalization
- Hands-on exposure to edge computing or CDN execution environments
- Track record of taking platforms or products from 0 to 1
- Ability to translate undefined product goals into scalable technical designs
- Experience using AI development tools such as GitHub Copilot, LLM-powered workflows, or agentic coding assistants
- Ability to thrive in a fast-moving, startup-like setting with evolving requirements

Technology Environment Backend: Java, Spring Boot

Cloud: AWS

Edge: Edge workers, CDN-layer compute, Lambda@Edge

Data & AI: Python, Databricks, ML model registry

Languages: Java, JavaScript/TypeScript, Python

Development Tools: GitHub Copilot and AI-assisted engineering workflows

Who Will Thrive in This Role?

This opportunity is ideal for an engineer who:

- Builds AI-enabled platforms rather than simply consuming AI tools
- Uses LLMs and AI development tools to improve engineering speed and quality
- Enjoys ambiguity, rapid prototyping, and iterative architecture
- Influences teams through technical depth, system design, and production code
- Works effectively across engineering, data science, product, and partner organizations

📌 Java Architect/Principal Software Engineer (Toronto)
🏢 DynPro
📍 Toronto