Platform Engineering Leader (AI)

Location: Hybrid in Toronto, Vancouver, or Calgary, Canada

Base salary: $130,000–$170,000 per year, depending on experience.

Company

hirify.global develops an AI-powered fraud and risk platform with real-time fraud detection and anti-money laundering capabilities.

What you will do

• Own the technical direction of the real-time detection platform, including streaming, storage, and machine learning training pipelines.
• Translate product and engineering roadmaps into technical plans, milestones, and execution priorities.
• Lead architecture reviews, make technical trade-offs, and document key decisions.
• Write and review code, debug production issues, and support incident response.
• Mentor engineers and improve system design, code quality, operational excellence, and technical execution.
• Define and build safe, verifiable AI-agent and LLM-assisted tools for triage, root-cause analysis, alert summarization, and engineering operations.

Requirements

• 8+ years of software development experience and 2+ years of technical leadership experience.
• Deep production experience with Java, plus working proficiency in Python and Shell scripting.
• Experience designing, building, shipping, and operating distributed real-time systems at scale.
• Strong knowledge of computer systems, relational databases, SQL, multithreading, and concurrency.
• Hands-on experience with Cassandra, Yugabyte, Flink, Spark, or Kafka, plus experience with the Spring Framework.
• Bachelor’s degree in Computer Science or a related field; experience with production AI coding tools and rigorous output verification.

Nice to have

• Experience in fraud, risk, payments, financial services, or other high-impact domains.
• Experience owning machine learning platforms or large-scale training pipelines.
• Experience with Kubernetes, LLM APIs, agent frameworks, tool calling, RAG, or MCP.
• Experience with evaluations for non-deterministic systems, hiring, managing, mentoring, or test-driven development.

Culture & Benefits

• Open, positive, collaborative, and results-driven engineering environment.
• Health insurance, paid time off, and equity.
• Work on large-scale fraud detection, machine learning infrastructure, and data processing systems.