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Siri InfoSolutions Inc
Java ArchitectSiri InfoSolutions Inc • toronto, ON, Canada
Java Architect

Java Architect

Siri InfoSolutions Inc • toronto, ON, Canada
12 hours ago
Job type
  • Full-time
  • Quick Apply
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.
  • JWT/JWS, PKI, OAuth 2.0, bot detection, or token verification.
  • 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.
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