Senior AI Platform Engineer

Janus Henderson Investors•Denver, CO

23h•$195,000 - $230,000•Hybrid

About The Position

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.

Requirements

At least five years in platform engineering, software engineering, DevOps, SRE, or cloud engineering, including building and operating shared services used by multiple teams.
Strong automation skills in Python or a comparable language, and hands-on experience with a major cloud, ideally Azure, including infrastructure as code, CI/CD, identity, RBAC, and secret management.
Production experience with LLM APIs or AI platforms, covering model access, quotas, rate limits, observability, and provider change management.
Hands-on administration of a major enterprise SaaS or productivity platform at tenant scale, including policy configuration, licence and entitlement management, staged feature enablement, and phased rollout to a large user base.
Experience acting as technical owner for software vendors, covering selection, due diligence, licensing, renewals, and cost management.
Good judgement in a regulated environment, translating security, privacy, risk, and audit requirements into working technical controls, and explaining trade-offs clearly to engineers, control functions, and senior stakeholders.
High ownership and comfort with change. You can bring structure to an unfamiliar product, resolve dependencies across teams, and remain accountable after it enters production.

Nice To Haves

Azure AI Foundry, Azure OpenAI, Anthropic Claude, Microsoft 365 Copilot, GitHub Copilot, or Microsoft Copilot Studio.
Microsoft 365, Entra ID, Purview, and Power Platform administration, including admin-centre configuration, data-loss-prevention policies, and environment strategy.
Experience building or operating an AI gateway, inference-routing layer, or multi-provider model platform.
Terraform, Docker, Kubernetes, or Azure DevOps, and enterprise observability, ITSM, or FinOps platforms.
Financial-services or asset-management experience, including regulated data and third-party risk processes.

Responsibilities

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.
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.
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 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. Set, adjust, and enforce allowances through quotas, alerts, and access boundaries, and give budget owners the visibility to manage their own consumption.
Report on adoption, licence take-up, spend, and service quality in enough detail to support funding decisions, and identify underused licences and duplicated products.
Act as technical owner for AI software vendors, supporting selection, due diligence, licensing, renewals, and exit planning with Procurement, Legal, TPRM, and Finance, and track vendor roadmaps, deprecations, and security advisories.
Work alongside Percepta and other delivery partners while new platforms are built, and accept platforms into service only when ownership and controls are clear.
Partner with AI Engineering and Forward Deployed Engineering so teams self-serve approved tools and models; with AI Governance Implementation, Risk, and AI Security to turn policy into automated controls; with AI Architecture to stay aligned to the target architecture; and with the AI Enablement Partners so training matches what the platform permits.

Benefits

Hybrid working and reasonable accommodations
Generous Holiday policies
Excellent Health and Wellbeing benefits including corporate membership to Wellhub
Paid volunteer time to step away from your desk and into the community
Support to grow through professional development courses, tuition/qualification reimbursement and more
Maternal/paternal leave benefits and family services
Unique employee events and programs including a 14er challenge
Complimentary beverages, snacks and all employee Happy Hours
competitive compensation
pension/retirement plans
various health, wellbeing and lifestyle benefits