Lead, Data Development, AI Platform | Chef(fe), Développement des données – Plateforme d’IA
at Hootsuite
- Seniority
- Lead Manager
- Location
- Ottawa, Canada; Toronto, Canada; Waterloo, Canada, Montreal, Quebec, Canada
- Posted
- 18d ago
gollm
at Hootsuite
<p>We are looking for a Lead, Data Development, AI Platform to lead the team building and operating the technical platform behind Hootsuite's Analytics MCP. This includes routing infrastructure, orchestration services, agent infrastructure, and data pipelines that enable reliable AI-driven analysis at scale. You will set technical direction for the team, strengthen engineering practices, and translate target architecture and integration standards into secure, production-grade systems that Data Analytics & AI teams can confidently build on.</p> <p>This is a hands-on technical leadership role. You will stay close to the code while owning delivery outcomes, engineering quality, and the team's culture of craft and accountability. You will develop strong, well-reasoned recommendations on how the platform and orchestration architecture should evolve, seek approval at the Senior Manager and Director level, and then guide the team through disciplined execution. You will also partner closely with AI Context & Integration and AI Data Architecture to ensure the platform, context layer, semantic layer, and downstream agent workflows operate as one coherent system.</p> <h4><strong>WHAT YOU’LL DO:</strong></h4> <ul> <li>Lead the design and delivery of the orchestration layer that connects the Analytics MCP platform across its most complex surfaces, including query execution across schemas and models, federated data access between the data warehouse and external source systems, and multi-step agent workflows for cross-functional business processes. </li> <li>Develop clear technical recommendations for platform and orchestration architecture evolution, align those recommendations with Senior Manager and Director-level direction, and guide the team through disciplined execution within the approved architecture.</li> <li>Own the operational reliability, scalability, quality, and observability standards for core Analytics MCP components, including routing and agent infrastructure. Guide the team to build and operate these systems to production standards, lead incident response and root-cause analysis, and maintain a high code-quality bar through active review, mentorship, and operational discipline.</li> <li>Set and uphold standards for data pipelines built for agent and programmatic consumption rather than traditional dashboard delivery, ensuring the data AI systems depend on is high-quality, well-documented, testable, observable, and dependable at the source.</li> <li>Drive technical build and implementation of internal tooling and agents that improve AI Engineering workflows such as build, deployment, monitoring, diagnostics, and operational support, within the architecture and requirements defined by the Senior Manager.</li> <li>Set the team's engineering standards and ways of working, while developing team members through coaching, regular 1:1s, hands-on code review, and clear feedback that strengthens both technical capability and career growth. Coordinate with the Senior Manager on performance and career development for team members.</li> <li>Collaborate closely with AI Context & Integration and AI Data Architecture to ensure platform, orchestration, and data pipeline changes integrate cleanly with the context layer, semantic layer, governed data models, and downstream agent workflows.</li> <li>Perform other related duties as assigned.</li> </ul> <p><strong>WHAT YOU’LL NEED:</strong></p> <ul> <li>8+ years of hands-on software, data, or AI platform engineering experience, or equivalent combination of education and experience, including senior IC or technical leadership roles where you influenced technical direction, system design, and delivery outcomes.</li> <li>Experience leading or mentoring a small engineering team, including setting technical direction, running code reviews, supporting individual growth, holding accountability for team-level delivery, and balancing hands-on contribution with delegation and unblocking.</li> <li>Strong hands-on programming capability across backend services, APIs, data pipelines, or platform infrastructure, with the ability to build reliable, maintainable systems that meet production standards.</li> <li>Experience building or operating orchestration across systems, such as multi-step process coordination, query execution across multiple data sources, external system integration, workflow automation, or agent workflow orchestration, with the judgment to recommend practical architecture choices.</li> <li>Working knowledge of AI and LLM-based systems, including how agents, tools, context interfaces such as MCP, and orchestration layers work together to produce reliable outputs.</li> <li>Experience building data pipelines for programmatic or agent consumption, with strong attention to source-level quality, documentation, testing, observability, and operational maintainability.</li> <li>Familiarity with platform reliability practices, including observability, monitoring, debugging, security integration, root-cause analysis, performance tuning, and production support at scale.</li> <li>Influence and storytelling: Ability to influence without direct authority by using well-reasoned technical recommendations, clear tradeoff analysis, and a compelling narrative that helps others understand the path forward.</li> <li>Inclusive Leadership: Builds inclusive, cohesive teams that apply diverse perspectives to solve complex problems and achieve shared goals.</li> <li>Play to Win: Delivers results through others by establishing clear direction, creating accountability, removing blockers, and helping team members do their best work.</li> <li>Long Range Planning: Identifies the technical, organizational, and dependency risks relevant to long-range goals, and builds integrated plans that translate vision into executable work.</li> <li>Enablement: Challenges and supports others to deliver results while developing new capabilities. Successfully grows the capacity, capa