Staff Technical Program Manager (AI)

Location: Vancouver, Canada

Company

hirify.global provides AI-powered IT management and cybersecurity software for managed service providers and internal IT organizations worldwide.

What you will do

• Lead enterprise-scale data and AI platform programs across multiple engineering and product organizations.
• Define execution plans, milestones, dependencies, governance mechanisms, and measurable outcomes.
• Coordinate delivery across data engineering, ML engineering, applied AI, product, security, and infrastructure teams.
• Manage technical, organizational, and data-specific risks, including model readiness, data quality, pipeline reliability, and infrastructure dependencies.
• Provide executive-level reporting on milestones, blockers, risks, and overall program health.
• Improve delivery predictability and contribute to TPM operating models and best practices for data and AI programs.

Requirements

• Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related technical field.
• 10+ years of experience leading complex technical programs in SaaS, cloud, or enterprise software environments.
• Experience with data engineering, ML infrastructure, AI/ML product delivery, or data platform development.
• Ability to influence across organizations without direct authority and manage complex cross-functional dependencies.
• Strong communication, analytical, and problem-solving skills, with the ability to work in fast-paced and ambiguous environments.

Nice to have

• Familiarity with Snowflake, dbt, Spark, Kafka, Airflow, SageMaker, Vertex AI, MLflow, or similar platforms.
• Experience coordinating LLM integration, RAG pipelines, or AI feature delivery in a product context.
• Experience with platform engineering, cloud infrastructure, or data governance programs.
• Familiarity with Agile or hybrid delivery methodologies in data and ML contexts.

Culture & Benefits

• Work within a global software organization serving customers in more than 20 countries.
• Collaborate with engineering, product, data science, architecture, operations, and executive stakeholders.
• Contribute to AI-driven product experiences and internal data capabilities.