Software Engineer, AI - 12 month Contract

Pelmorex (The Weather Network / MétéoMédia) reaches millions of Canadians every day and operates one of the country's most trusted information services, including the Alert Ready emergency alerting system. Our newly formed AI & Data Solutions team exists to turn that scale, data, and trust into a competitive advantage across three fronts: empowering our workforce with AI, building custom AI solutions for the business, and monetizing our data. This is an early, ground-floor role on a small, high-leverage team. You'll have an unusually direct line of sight from the code you write to the business outcomes it drives, and the latitude to shape how AI gets built and shipped across the company.

Be part of the team that takes working prototypes to production quality. We are building active AI tools powering key workflows for both internal partners and external customers requiring robust, production-grade systems complete with resilient infrastructure, automated guardrails, enterprise fallbacks, and end-user support. You will own the end-to-end production path for approved products, shipping high-impact services one launch at a time by swapping demo shortcuts for reliable engineering standards that can scale.

This is a software development and infrastructure role that leverages multi-modal LLM APIs (text, image, and video). We expect you to leverage AI natively to architect, test, and ship modern production systems - identifying bottlenecks, setting higher benchmarks, and continuously raising the bar.

Please note, that is is a 12 month contract role and we are only considering candidates who are eligible to work in Canada and can work in a Hybrid model at our Oakville location.

• Transition proof-of-concept prototypes to production-grade systems, managing auth, data persistence, CI/CD pipelines, infrastructure, test suites, and operational runbooks

• Design, build, and maintain scalable backend services and RESTful APIs

• Architect systems for high availability, reusability, and fault tolerance using retries, circuit breakers, timeouts, and automated fallback mechanisms

• Establish strict guardrails to enforce response accuracy, catalog constraints, cost ceilings, and compliance with brand guidelines

• Implement end-to-end LLM telemetry and observability (e.g., Langfuse) to track prompts, token usage, latency, spend, and user sessions

• Develop multi-tier caching strategies across responses, embeddings, and media to minimize latency and redundant API expenditure

• Integrate multimodal generative AI workflows into production pipelines, managing queues, rate limits, and graceful degradation paths

• Deploy and optimize cloud infrastructure (AWS/GCP), overseeing secret management, storage, compute resources, and cost management

• Drive code quality and reliability through automated unit and integration testing delivered via continuous integration pipelines

• Maintain system health and production uptime through comprehensive logging, metrics, tracing, and on-call rotation support

• Author and maintain operational documentation for deployment, incident recovery, and infrastructure spend

• Leverage AI developer tools to accelerate delivery while maintaining rigorous engineering, review, and testing standards

• Own feature lifecycles end-to-end, from initial release to ongoing post-launch production support

Roles, responsibilities and duties may evolve and change over time.

• 5+ years of demonstrated hands-on track record architecting, running, and maintaining production backend microservices and RESTful APIs

• Proven experience hardening quick experimental prototypes into production-grade, highly available systems with robust authentication, storage, and reliability standards

• End-to-end technical ownership over software quality, test coverage, and architecture, leveraging AI developer tools to accelerate output without sacrificing engineering rigour

• Deep expertise deploying and managing cloud infrastructure on AWS or GCP, including identity management, compute, storage resources, and cost control

• Production infrastructure fluency using Docker, CI/CD automated deployment pipelines, environment isolation, networking, and zero-downtime rollback strategies

• Commitment to operational excellence and system uptime through strict performance thresholds, automated graceful degradation paths, and resilience design

• Experience establishing operational guardrails, response validation schemas, rate limits, retries, multi-tier caching, and fallback mechanisms for external services

• Direct experience integrating LLM model inference into live pipelines across text, image, or video multimodal workflows

• Track record implementing comprehensive LLM telemetry (e.g., Langfuse) to track prompt metrics, token consumption, latency, and operational spend

• Skill in architecting multi-tier caching architectures across memory and disk tiers to minimize API costs and drive down service latency

• Readiness to participate in on-call rotation support and drive fast incident recovery for production systems

• Hands-on mastery across core technical components of our engineering stack:

• High adaptability and agility when mastering new frameworks, technologies, and modern developer tooling

• Strong proficiency in Python or Node.js backend development (Go experience welcomed)

• Experience with relational databases (Postgres), vector search indexes, and caching systems (Redis)

• Building scalable API services using modern web frameworks like FastAPI

• Containerized deployments with Docker and orchestration platforms like Kubernetes

• Cloud platform operations across major ecosystems including AWS and GCP

• Delivering continuous integration and delivery pipelines via automated build tooling

• Driving software reliability through continuous automated unit, integration, and end-to-end testing

• Sufficient frontend expertise (React, JavaScript) to author and maintain internal tooling dashboards

• Solid comprehension of the generative AI application development lifecycle

• Familiarity serving open-source ML models via engines like vLLM or llama.cpp

• Bachelor's degree in Computer Science, Software Engineering, or equivalent practical industry background

• Demonstrated passion for hardening production-grade services serving active end users beyond initial experimental prototypes

• Rigorous commitment to test coverage prior to deployment, with proven experience executing zero-downtime, stress-free rollback strategies if necessary

• Ability to demonstrate full technical ownership moving local proofs-of-concept into live RESTful APIs with auth, multi-tier caching, telemetry, fallbacks, and runbooks

• Proven capability optimizing multimodal text and video generative workflows to satisfy strict cost ceilings and latency thresholds via queues, caching, and timeouts

• Exceptional cross-functional communication skills, fostering seamless collaboration across engineering and product stakeholders

• Pragmatic, hands-on orientation combined with an uncompromising commitment to engineering standards and complete code ownership

• High energy, collaborative spirit, and a relentless focus on shipping impactful business results

• Course Reimbursement Program 📚 We want you to keep learning, so we can too
• Open and transparent communication, including All Hands Meetings with our CEO
• Pelmorex Learning Academy 🏫
• Your mental health is important to us! 🧠 We partner with our benefits provider for virtual counseling sessions
• Frequent employee pulse surveys 📝 we value your feedback so we can continue to make Pelmorex a great place to work!
• Free online doctor visits 👩‍⚕️ with Maple Online Healthcare
• While we encourage 1:1 conversations, we recognize that not everyone is comfortable with speaking up 🗣 We have an anonymous reporting platform to ensure everyone’s voice is heard