Lead, Data Development, AI Platform - Hootsuite, Vancouver

AI Summary

Hootsuite is seeking a Lead, Data Development, AI Platform in Vancouver, Canada. This role involves leading a team to build and operate the technical platform behind Hootsuite's Analytics MCP, including routing infrastructure, orchestration services, agent infrastructure, and data pipelines.

Key duties include setting technical direction, strengthening engineering practices, and translating target architecture into secure, production-grade systems. Top requirements include 8+ years of software, data, or AI platform engineering experience, including technical leadership, and strong hands-on programming capability, particularly with orchestration across systems and AI/LLM-based systems.

About the Role at Hootsuite

This pivotal role at Hootsuite in Vancouver is for a Lead, Data Development, AI Platform, focusing on the technical platform powering Hootsuite's Analytics MCP. The successful candidate will lead a team responsible for building and operating critical infrastructure, including routing, orchestration services, agent infrastructure, and robust data pipelines. This technical leadership position involves setting the architectural direction for sophisticated systems, ensuring secure and production-grade solutions that Data Analytics & AI teams can confidently leverage. The role demands a hands-on approach, balancing coding with ownership of delivery outcomes and engineering quality, including developing well-reasoned recommendations for platform and orchestration architecture evolution.

You will stay close to the code while owning delivery outcomes, engineering quality, and fostering a culture of craft and accountability within the team. This includes developing strong, well-reasoned recommendations on how the platform and orchestration architecture should evolve, seeking approval at the Senior Manager and Director level, and then guiding the team through disciplined execution. Close partnership with AI Context & Integration and AI Data Architecture teams is essential to ensure the platform, context layer, semantic layer, and downstream agent workflows operate as one coherent system, including all necessary integrations.

Key Responsibilities and Technical Leadership

As the Lead, Data Development, AI Platform, you will be instrumental in designing and delivering the orchestration layer that seamlessly connects the Analytics MCP platform across its most complex surfaces. This includes managing query execution across various schemas and models, facilitating federated data access between the data warehouse and external source systems, and orchestrating multi-step agent workflows for cross-functional business processes. You will develop clear technical recommendations for the platform and orchestration architecture's evolution, securing alignment with Senior Manager and Director-level direction, and then guiding your team through disciplined execution within the approved architecture.

A core aspect of this role involves owning the operational reliability, scalability, quality, and observability standards for critical Analytics MCP components, including routing and agent infrastructure. This includes guiding the team to build and operate these technical systems to production standards, leading incident response, and maintaining a high code-quality bar through active review and mentorship. Furthermore, you will set and uphold standards for data pipelines specifically built for agent and programmatic consumption, ensuring the data AI systems depend on is high-quality, well-documented, testable, observable, and dependable at the source. This role also involves driving the technical build and implementation of internal tooling and agents that enhance AI Engineering workflows, such as build, deployment, monitoring, diagnostics, and operational support, all within the defined architecture and requirements. Collaboration with AI Context & Integration and AI Data Architecture is crucial to ensure platform, orchestration, and data pipeline changes integrate cleanly with the context layer, semantic layer, governed data models, and downstream agent workflows, creating a coherent system.

Required Skills and Experience

Candidates for this Lead, Data Development, AI Platform role should possess a minimum of eight years of hands-on software, data, or AI platform engineering experience, or an equivalent combination of education and experience. This background should include senior individual contributor or technical leadership roles where you demonstrably influenced technical direction, system design, and delivery outcomes. Experience leading or mentoring a small engineering team is essential, including setting technical direction, conducting code reviews, supporting individual growth, and holding accountability for team-level delivery while balancing hands-on contribution with delegation.

A strong hands-on programming capability across backend services, APIs, data pipelines, or platform infrastructure is required, with the proven ability to build reliable, maintainable systems that meet production standards. Crucially, candidates must have experience building or operating orchestration across various technical systems, such as multi-step process coordination, query execution across multiple data sources, external system integration, workflow automation, or agent workflow orchestration, demonstrating sound judgment in recommending practical architecture choices. A working knowledge of AI and LLM-based systems is also necessary, including understanding how agents, tools, context interfaces like MCP, and orchestration layers collaborate to produce reliable outputs. Experience building data pipelines for programmatic or agent consumption is key, with strong attention to source-level quality, documentation, testing, observability, and operational maintainability. Familiarity with platform reliability practices, including observability, monitoring, debugging, security integration, root-cause analysis, performance tuning, and production support at scale, is also highly valued. The ability to influence without direct authority through well-reasoned technical recommendations, clear tradeoff analysis, and compelling narratives is a significant asset for this leadership position.