Technical Product Manager (AI)

TL;DR

Technical Product Manager (AI): Leading the full lifecycle of AI and data initiatives with an accent on data management, agentic system orchestration, and evaluation frameworks. Focus on scalable architectures that support data ingestion, transformation, context retrieval, and multi-agent coordination.

Location: Hybrid model with four days per week in our Toronto office.

Salary: $130,000 - $160,000 (CAD)

Company

hirify.global helps Fortune 500 companies unlock growth with cutting-edge digital solutions that transform industries and create measurable business impact.

What you will do

• Own and drive the end-to-end lifecycle of AI- and data-intensive technical initiatives across multiple products.
• Define and evolve data management strategy, including data modeling standards, pipeline requirements, governance, lineage, and quality frameworks.
• Lead product strategy for agentic systems, including orchestration layers, tool usage patterns, memory/context management, guardrails, and fallback strategies.
• Establish and operationalize evaluation frameworks for AI products (LLM evals, benchmarking, human-in-the-loop review, automated scoring, drift monitoring).
• Partner with engineering to design scalable architectures that support data ingestion, transformation, context retrieval, and multi-agent coordination.
• Translate business objectives into clear technical specifications spanning APIs, data contracts, orchestration logic, and observability requirements.

Requirements

• Bachelor’s degree in Computer Science, Information Technology, Engineering, or a related technical field.
• 2–5 years of experience in technical product management, preferably in AI, ML, or data platform environments.
• Strong understanding of data architecture and data management principles, including data modeling, governance, lineage, quality monitoring, and cloud data platforms.
• Demonstrated experience working on AI-powered or agent-based products, including orchestration patterns and evaluation methodologies.
• Familiarity with LLM concepts such as context windows, retrieval augmentation (RAG), prompt orchestration, tool calling, memory management, and guardrails.
• Deep understanding of cloud computing platforms, distributed systems, APIs, and integration patterns.

Culture & Benefits

• Hybrid Flexibility: Enjoy a hybrid model with four days per week in our Toronto office.
• Downtown Toronto Office: Work in the heart of the city.
• Comprehensive Benefits: We cover 100% of health, dental, and vision insurance premiums for you and your dependents which means no out-of-pocket costs.
• Growth & Learning: Access extensive learning and development resources to keep leveling up your skills.