Software Engineer II (Agentic AI)

Location: Hybrid in Toronto, Canada

Salary: CA$135,000–CA$175,000 annual base salary, plus equity and an annual bonus.

Company

hirify.global builds identity trust infrastructure for the digital economy, verifying identities in real time and preventing fraud for businesses, governments, and consumers.

What you will do

• Build components of a vendor-agnostic agent platform, including orchestration, tool use, memory, and runtime systems.
• Develop evaluation and reliability tooling such as metrics, harnesses, and production pipelines.
• Implement safety and governance controls, including guardrails, policy enforcement, and human-in-the-loop reviews.
• Build retrieval, data grounding, and memory components that improve agent accuracy and contextual awareness.
• Prototype agent behaviors for planning, multi-step execution, and coordination across tools and services.
• Partner with product and engineering teams to deliver agent-powered workflows and refine secure, observable, scalable design patterns.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Computer Engineering, Machine Learning/AI, or a related field, or equivalent practical experience.
• At least 2 years of professional software engineering experience in distributed systems, backend platforms, infrastructure, or comparable environments.
• Strong foundational knowledge of large language models and agentic AI, including architectures, prompting, orchestration, tool use, and evaluation.
• Understanding of GPU computing and model-serving infrastructure, including technologies such as CUDA, vLLM, Ollama, TensorRT-LLM, or Triton Inference Server.
• Knowledge of distributed systems fundamentals, including concurrency, fault tolerance, observability, and performance, plus proficiency in Java, Go, Python, or a similar backend language.
• Ability to work in ambiguous early-stage problem spaces and collaborate with product, data science, platform, and security partners.

Nice to have

• Experience with multi-agent systems, workflow orchestration, distributed coordination, or agent platforms.
• Experience with LLM routing, caching, fine-tuning, evaluation frameworks, experimentation platforms, or model benchmarking.
• Experience with AI safety, security, policy systems, guardrails, content filters, or responsible AI frameworks.
• Experience with retrieval systems, knowledge graphs, enterprise data platforms, or LLM infrastructure.

Culture & Benefits

• Hands-on work on a zero-to-one agentic AI platform with exposure to production architecture and operations.
• Collaboration with senior and staff engineers who provide architectural direction.
• Compensation includes equity, benefits, and an annual bonus.
• Equal opportunity workplace with accommodation support available during the hiring and onboarding process.