Software Engineer, AI

Location: Canada — Toronto, Vancouver, Oakville, Calgary, Ottawa, and other listed Canadian locations

Base salary: CAD 91,200–114,000 annually, plus target incentives

Company

hirify.global is an IT solutions provider delivering secure cloud, AI, software, and digital workplace solutions to organizations in Canada and the United States.

What you will do

• Design, build, test, deploy, and support production-ready AI applications and technical workstreams.
• Develop AI solutions using LLMs, RAG, semantic search, document and data processing, and agentic workflows.
• Build secure backend services, APIs, integrations, and cloud-native components connected to enterprise systems and data.
• Optimize ingestion, chunking, embeddings, retrieval, prompting, grounding, tool use, memory, and workflow orchestration.
• Evaluate and productionize solutions through testing, resiliency, observability, performance optimization, monitoring, and responsible AI controls.
• Contribute to architecture and code reviews, CI/CD, infrastructure-as-code, containerized or serverless deployments, documentation, and customer collaboration.

Requirements

• 4–6 years of software engineering experience, including at least 2 years developing AI, machine learning, or generative AI solutions.
• Strong Python skills plus experience with TypeScript/JavaScript, Java, C#, or Go.
• Experience with backend services, APIs, integrations, databases, authentication and authorization, and asynchronous or event-driven applications.
• Hands-on experience with Azure, AWS, or Google Cloud and modern AI platforms or models.
• Practical experience with LLM applications, RAG, embeddings, vector search, prompt engineering, AI agents, evaluation, and data pipelines.
• Experience with modern web applications, software architecture, secure development, responsible AI, communication, estimation, and Agile delivery.

Nice to have

• Docker, Kubernetes, serverless architectures, messaging, caching, workflow orchestration, or distributed systems experience.
• Git, automated testing, CI/CD, infrastructure-as-code, observability, MLOps, or LLMOps experience.
• Traditional machine learning, model fine-tuning, data science workflows, scalable AI inference, or relevant certifications.

Culture & Benefits

• Collaborative, inclusive, and high-performing work environment.
• Medical and dental care, employee and family assistance, life and disability insurance.
• RRSP/DPSP retirement savings plan with company matching.
• Vacation, sick leave, holidays, parental leave, volunteer days, and bereavement leave.
• Employee discount program and flexible workday planning.
• Remote onboarding, digital interviews, and employment accommodations during hiring.

Hiring process

• Digital interviews are used during recruitment.
• Before joining, candidates undergo a criminal record check, education verification, and reference checks.
• Remote onboarding is provided after hiring.