Senior AI Platform Engineer

Why work for us? A career at Janus Henderson is more than a job, it’s about investing in a brighter future together. Our Mission at Janus Henderson is to help clients define and achieve superior financial outcomes through differentiated insights, disciplined investments, and world-class service. We will do this by protecting and growing our core business, amplifying our strengths and diversifying where we have the right. Our Values are key to driving our success, and are at the heart of everything we do: Clients Come First - Always | Execution Supersedes Intention | Together We Win | Diversity Improves Results | Truth Builds Trust If our mission, values, and purpose align with your own, we would love to hear from you! Your opportunity Janus Henderson is undertaking a firm-wide AI transformation to become the most technologically sophisticated asset manager in the industry, and it has to move quickly without compromising security, resilience, or regulatory obligations. Our AI capability sits in a single centralised function under the Head of AI. AI Technology owns the AI product and workload plane — the software, models, gateways, and controls used to build and run AI across the firm — and AI Platforms is the team within it that owns the tooling estate itself. As Senior AI Platform Engineer, reporting to the Head of AI Technology, you will own the day-to-day engineering and lifecycle of that estate, from Azure AI Foundry and the AI model gateway through to Claude and our Copilot services. You will assess new products, run controlled pilots, automate onboarding, and turn selected tools into supported services. You will also hold the administrator seat for Microsoft 365 Copilot, GitHub Copilot, and Copilot Studio, controlling their administrative settings and the plan by which they are deployed. This is a hands-on role with broad ownership, working across AI Engineering, AI Architecture, AI Governance Implementation, AI Security, Central Technology, Procurement, and the AI Enablement Partners. You will be expected to understand both the code and the contract: how a tool integrates, how it behaves in production, what it costs, and how it is controlled. The portfolio will change quickly, so the role needs sound judgement and the ability to turn one-off approval work into a repeatable onboarding path. What success looks like • New AI products reach a decision quickly through a repeatable risk-based path, and teams self-serve — engineers and business users consume approved tools and models through documented patterns rather than one-off requests to you. • The model gateway is dependable. Availability, latency, quotas, and cost are visible, and provider change is absorbed without breaking the teams that consume it. • Copilot capability lands deliberately, with licences, cohorts, and features released to a plan and the required controls evidenced first. • Spend is defensible. Token consumption and licence take-up are attributed by team, agent, and provider, budgets are enforced where they need to be, and you act on what is underused or duplicated. Your responsibilities Engineer and operate the AI tooling estate • Build, configure, and operate shared AI software and platform services used by engineering teams, business users, agents, and applications. • Own the technical lifecycle of AI tools from discovery and pilot through onboarding, upgrades, support, renewal, and retirement. • Automate provisioning, configuration, policy enforcement, and evidence collection using APIs, infrastructure as code, and CI/CD. • Provide L2 support, maintain runbooks and recovery procedures, and escalate to vendors or Central Technology where the issue sits outside the AI workload plane. Run the model gateway and onboard AI software • Engineer and operate the AI Team’s model gateway and routes to hosted and external model providers, managing integrations, credentials, quotas, routing rules, fallback, and rate limits. • Implement identity, role-based access, entitlements, and secure secret handling with enterprise IAM and AI Security, and monitor availability, latency, errors, usage, and policy breaches with auditable records of model access, decisions, and costs. • With AI Security and AI Governance Implementation, establish a risk-based process for evaluating and onboarding new AI products, model providers, versions, and platform features, leading the technical discovery, pilots, and production-readiness reviews, and distinguishing routine upgrades from materially new or higher-risk capabilities. • Work with AI Architecture on buy-versus-build decisions and encode approved controls into the platform. Administer and deploy our Copilot services • Act as service owner and administrator for Microsoft 365 Copilot, GitHub Copilot, and Copilot Studio, controlling every administrative setting and policy through delegated administrator roles in the tenants Central Technology operates. • Own the deployment plan: licence assignment, cohort sequencing, environment and connector strategy, agent publishing routes, and the order in which capability reaches each part of the firm. • Define the Copilot roadmap with the Principal AI Architect and AI Security, deciding which vendor features are made available and to whom, and staging capability until the required controls are evidenced. • Govern the Copilot Studio maker experience — environments, data-loss-prevention policies, connectors, and publishing approval — so business users build agents inside agreed guardrails. Own telemetry, token budgets, licences, and vendors • Own and maintain the usage, cost, and token telemetry across every AI system — the model gateway, Copilot services, Azure AI Foundry, and external providers — so consumption is attributed consistently to users, teams, agents, applications, and providers, and keep it accurate as the estate changes. • Administer token budgets at the granularity the firm needs, whether by user, team, agent, application, or use case.