League is building the agentic platform for healthcare: the harness, orchestration, and runtime that turn frontier and healthcare-native models into deployed intelligence inside member-facing care experiences

This is the layer that sits between the models and the member; the one that decides what an agent can do, what it can’t, how it composes with other agents, and how its work shows up in the product

We’re looking for a VP, AI Platform Engineering to lead the team that builds it. This role leads engineering for League’s agentic platform — the multi-agent orchestration runtime, agent harness, evaluation and guardrail infrastructure, and the developer surface that other teams at League use to ship domain agents into production

It is a peer to the AI Models leadership that owns the intelligence layer (Generalized Healthcare Intelligence: League’s portfolio of healthcare-native SLMs), the Data Platform leadership that owns the data substrate, and the AI Product leadership that owns the consumer-grade agentic experience

Together these functions form the Data & AI First Team that owns League’s bet on healthcare AI end-to-end The agentic platform: You own the engineering of League’s multi-agent orchestration runtime; the harness, framework, model-routing layer, and evaluation and guardrail infrastructure that runs every agent League ships The platform is the layer between the models and the member; how good it is determines how much intelligence League can actually deploy The developer surface: You own the engineering of the platform that League’s teams and League’s customers use to build, simulate, configure, and evaluate agents; the SDK, tooling, simulation environment,



and configuration surfaces that turn the agentic harness into a product the rest of League and the market build on

Success is measured by how much agent functionality ships across League and across League’s customers without going through your team The team: You lead the engineers and managers who build the agentic platform.

Building the bench is part of the work: this org will grow with the platform, and your hiring bar will set the ceiling for what we ship The First Team: You sit on League’s Data & AI leadership team alongside the leaders of AI Models, Data Platform, and AI Product, where the bets that decide League’s healthcare AI strategy get made The work runs both ways: shaping cross-cutting decisions on model strategy, evaluation methodology, and data contracts inside League, and carrying technical credibility into the conversations with customers and partners

Use AI tools as part of your daily workflow to enhance productivity, problem-solving, and decision-making (e.g., drafting, analysis, coding, research, or process automation)

Apply judgment and accountability when using AI by reviewing outputs for accuracy, bias, and quality before use

Continuously learn and adapt as new AI tools and capabilities emerge, incorporating them into your ways of working

Identify opportunities to improve how work gets done from personal productivity to team-level workflows by leveraging AI effectively





Operate with strong data responsibility and security awareness, especially when working with sensitive or regulated information

How this scales by level:

Benefits Flexible medical and dental plans

Health, lifestyle, learning and family spending accounts

401(k) and RRSP matching programs

Employee stock option program (ESOP)

Versatile time off

Generous leaves (including parental and sabbatical)- Strong track record building high-performing engineering cultures and developing senior technical talent

Excellent communication and executive presence, with the ability to influence technical, customer, and executive audiences

Experience leading platform engineering teams that enable multiple product and engineering organizations

Deep understanding of AI platform architecture, infrastructure, scalability, reliability, and operational excellence

Pragmatic operator mindset with a focus on solving high-impact problems and shipping customer-ready solutions

Strong understanding of the modern AI ecosystem, including emerging platform, tooling, and deployment patterns

Experience partnering cross-functionally across Product, Data, Infrastructure, Security, and Go-to-Market teams

Track record of delivering measurable business and operational impact through AI and platform engineering initiatives

Strong technical judgment with the ability to balance innovation, speed, and business value

Proven experience building and operating AI systems in production at enterprise scale

Demonstrated experience using AI tools in a practical, responsible way

Ability to balance efficiency with quality and sound judgment

Curiosity and openness to experimenting with new technologies

📌 Vice President of AI Platform Engineering (Quebec)
🏢 Socket.dev
📍 Quebec