Software Engineer, AI - 12 month Contract

Location: Hybrid work at the Oakville, Canada location; candidates must be eligible to work in Canada.

Company

hirify.global operates The Weather Network, MétéoMédia, and the Alert Ready emergency alerting system, reaching millions of Canadians with trusted weather and emergency information.

What you will do

• Transition AI proof-of-concept prototypes into production-grade systems with authentication, persistence, CI/CD, testing, infrastructure, and operational runbooks.
• Design, build, and maintain scalable backend services and RESTful APIs with high availability, fault tolerance, retries, circuit breakers, timeouts, and fallback mechanisms.
• Integrate multimodal LLM workflows across text, image, and video, including queues, rate limits, graceful degradation, guardrails, and response validation.
• Implement LLM telemetry and observability for prompts, token usage, latency, spend, and user sessions, including tools such as Langfuse.
• Develop multi-tier caching for responses, embeddings, and media; deploy and optimize AWS or GCP infrastructure, secrets, storage, compute, and costs.
• Own feature lifecycles, operational documentation, production support, incident recovery, logging, metrics, tracing, uptime, and on-call support.

Requirements

• 5+ years of hands-on experience architecting, operating, and maintaining production backend microservices and RESTful APIs.
• Experience hardening experimental prototypes into highly available production systems with authentication, storage, reliability standards, guardrails, response validation, rate limits, retries, caching, and fallbacks.
• Strong proficiency in Python or Node.js backend development; Go experience is welcomed.
• Deep experience with AWS or GCP, including identity management, compute, storage, networking, secret management, and cost control.
• Production infrastructure experience with Docker, Kubernetes, CI/CD deployment pipelines, environment isolation, automated testing, and zero-downtime rollback strategies.
• Experience with Postgres, vector search indexes, Redis, FastAPI, automated unit, integration, and end-to-end testing.
• Direct experience integrating LLM inference into live multimodal text, image, or video pipelines and implementing telemetry such as Langfuse.
• Frontend proficiency with React and JavaScript sufficient to maintain internal tooling dashboards.
• Understanding of the generative AI application development lifecycle and familiarity with serving open-source models through vLLM or llama.cpp.
• Readiness to participate in on-call rotation and support rapid production incident recovery.
• Bachelor’s degree in Computer Science, Software Engineering, or equivalent practical industry experience.
• Must be eligible to work in Canada and able to work in the hybrid Oakville model.

Nice to have

• Experience optimizing multimodal text and video generative workflows against strict cost and latency thresholds using queues, caching, and timeouts.
• Exceptional cross-functional communication and experience collaborating with engineering and product stakeholders.
• Experience moving local proofs of concept into live APIs with authentication, caching, telemetry, fallbacks, and runbooks.

Culture & Benefits

• 12-month contract with full-time employment and a flexible hybrid work environment.
• 17 paid days off, 13 personal days, summer hours, and an additional day off during the birthday month.
• RRSP retirement savings matching, health and personal spending accounts, including up to $500 for physical, mental, or financial well-being.
• Course reimbursement, hirify.global Learning Academy, virtual counseling, online doctor visits, and learning-focused workplace practices.
• Open communication, professional discussion of issues and timelines, quick delivery to real users, and an emphasis on inclusion, transparency, and experimentation.

Hiring process

• AI tools may be used for interview preparation and learning, but real-time AI assistance, live answer prompts, and automated response tools are not permitted during interviews.