Java/ Spring Boot Developer- Upgrade & Modernization

TMS; Toronto; On-site; CAD 140,000 - 190,000; Part time

Job summary

TMS is seeking a Staff/Principal Software Engineer to design and ship complex architectures from the ground up in a hands-on IC role located in Downtown Toronto, ON. The contract position requires strong coding and architectural influence, with focus on edge computing, AI/ML platforms, and AWS-based solutions.

The role emphasizes greenfield development, rapid prototyping, and collaboration with Data Science, Product, Engineering, and partner teams to deliver scalable backend services using Java

Qualifications

• 10+ years of experience building production-grade distributed systems.
• Strong Java and Spring Boot expertise.
• Strong system design and architecture experience.
• Proven experience taking greenfield projects from 0 to 1.
• Hands-on implementation experience - strong coder.
• Experience building features supporting ML inference pipelines, data normalization, feature pipelines, model serving, or similar AI/data platforms.
• Strong AWS experience across compute, storage, networking, and IAM.
• Experience with edge computing/CDN execution environments such as Edge Workers, CDN Functions, Lambda@Edge, or equivalent.
• Experience with microservices and event-driven architectures.
• Excellent communication and stakeholder management skills.

Responsibilities

• Design and build end-to-end signal flows, including edge detection, ingestion APIs, processing, storage, and downstream routing.
• Architect edge-layer solutions across edge-worker runtimes and CDN-layer compute for token detection, header manipulation, and signal capture with minimal latency impact.
• Build backend services using Java Spring Boot, including APIs, validation/normalization pipelines, data persistence, and platform foundations.
• Define integration patterns for third-party vendors, including identity and trust providers.
• Implement JWT validation, public-key caching, and deterministic signal ingestion.
• Build platform capabilities supporting ML inference, including structured data access layers, feature pipelines, and model-registry integration.
• Make technology decisions around storage, transport reliability, observability, security, and governance on AWS.
• Drive rapid prototyping, demos, iterative architecture refinement, and production implementation.
• Work closely with Data Science, Product, Engineering, and partner teams.

Skills

Java Spring Boot

System design

Distributed systems

Greenfield projects

Hands-on coding

AWS

Edge computing

Microservices

Communication

AI/ML platforms

GitHub Copilot

LLM-powered workflows

Tools

Edge Workers

CDN Functions

Lambda@Edge

GitHub Copilot

LLM-powered workflows

Job description

Job Title: Java Architect / Principal Software Engineer

Location: Downtown Toronto, ON

Hire Type: Contract

Role Summary

We are looking for a Staff/Principal Software Engineer who thrives in ambiguity, builds systems from the ground up, and ships quickly. This is a highly hands-on Individual Contributor (IC) role with significant architectural influence.

The ideal candidate will be responsible for both system architecture and hands‑on implementation, working at the intersection of edge computing, backend services, AI/ML platforms, and data science.

Key Responsibilities

• Design and build end‑to‑end signal flows, including edge detection, ingestion APIs, processing, storage, and downstream routing.
• Architect edge‑layer solutions across edge‑worker runtimes and CDN‑layer compute for token detection, header manipulation, and signal capture with minimal latency impact.
• Build backend services using Java Spring Boot, including APIs, validation/normalization pipelines, data persistence, and platform foundations.
• Define integration patterns for third‑party vendors, including identity and trust providers.
• Implement JWT validation, public‑key caching, and deterministic signal ingestion.
• Build platform capabilities supporting ML inference, including structured data access layers, feature pipelines, and model‑registry integration.
• Make technology decisions around storage, transport reliability, observability, security, and governance on AWS.
• Drive rapid prototyping, demos, iterative architecture refinement, and production implementation.
• Work closely with Data Science, Product, Engineering, and partner teams.

Must-Have Skills & Experience

• 10+ years of experience building production‑grade distributed systems.
• Strong Java and Spring Boot expertise.
• Strong system design and architecture experience.
• Proven experience taking greenfield projects from 0 to 1.
• Experience selecting technologies/frameworks and building the initial architecture from scratch.
• Hands‑on implementation experience - must be a strong coder, not an architecture‑only candidate.
• Experience building features supporting ML inference pipelines, data normalization, feature pipelines, model serving, or similar AI/data platforms.
• Strong experience with AI‑assisted development tools, such as GitHub Copilot, LLM‑powered workflows, or agentic coding assistants.
• Strong AWS experience across compute, storage, networking, and IAM.
• Experience with edge computing/CDN execution environments such as Edge Workers, CDN Functions, Lambda@Edge, or equivalent.
• Experience with microservices and event‑driven architectures.
• Excellent communication and stakeholder management skills.
• Ability to independently drive technical decisions in an ambiguous environment.

Critical Client Expectations

The client is specifically looking for candidates who:

• Have greenfield/0‑to‑1 project experience and have personally selected and established the technology framework.
• Are highly experienced with AI‑assisted development while remaining strong hands‑on engineers.
• Demonstrate exceptional system design and architecture capabilities.
• Have strong implementation and coding experience.
• Communicate clearly and confidently with technical and non‑technical stakeholders.
• Are naturally curious and probing - candidates should ask why, what, when, where, and how rather than simply agreeing with requirements.
• Can challenge assumptions, identify gaps, and propose thoughtful technical solutions.
• Thrive in a fast‑paced, startup‑like environment with evolving requirements.

Nice‑to‑Have

• Identity, trust, or security domain experience.
• Python experience for data engineering or scripting.
• Databricks or similar AI/data platform experience.
• Observability at scale, including distributed tracing, structured logging, and dashboards.
• Experience with multi‑party integration platforms or network services.
• Open‑source contributions or community involvement.