Senior AI Engineer

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!

Janus Henderson is undertaking a firm-wide AI transformation to become the most technologically sophisticated asset manager in the industry. Our AI capability sits in a single centralised function under the Head of AI, and AI Technology is the part of it that builds, governs, and runs the software.

AI Engineering is the core product and platform engineering team within it. Where Forward Deployed Engineering embeds with a business unit to solve one team’s problem, AI Engineering builds the enterprise products every other team depends on:
Nexus, our agentic workspace, where employees build, test, run, and manage governed AI applications, agents, and shared skills;
Accio, our centralised MCP server, which acts as a passthrough and logic centre for enterprise datasets, consuming other MCP servers and presenting them through one governed interface; and the orchestration, evaluation, and observability services beneath Libros and PRISM, two of the projects we are delivering with Percepta.

As a Senior Applied AI Engineer, reporting to the Principal AI Engineer, you will lead the delivery of major parts of that estate — designing and building agentic applications and platform services, taking them through evaluation and our AI governance checkpoints into production, then owning them once live. You will set implementation patterns alongside AI Architecture, review other engineers’ work, and be the person the team turns to when a production system behaves in a way nobody predicted.

You will also work beside Percepta’s engineers, making sure each platform enters service with a design the team understands and more than one person able to extend it.

You will also own the end-to-end build of business applications for specific parts of the firm — not only the horizontal products every team shares, but targeted applications built on the AI stack for a named business area, carried from first requirement through to a supported production service. Distribution is the first focus. Much of this work is deliberate SaaS decommissioning: where a capability currently bought as a SaaS subscription can be built in-house instead, you own that build end-to-end and see the displaced product retired, so the firm consolidates onto governed, in-house capability rather than paying for overlapping tools.

You will take the same approach into other business areas — trading, investment risk, client servicing, and operations among them — choosing the builds where owning the application gives the firm more control, lower cost, or capability no vendor sells.

Your toolkit spans Python and SQL, LLMs and agent frameworks, MCP, Azure AI Foundry through the AI Team’s model gateway, Snowflake and Microsoft Fabric, and Azure with Terraform, Docker, and CI/CD. AI Engineering is being established for the first time here, so you will shape how the team works rather than inherit a settled routine.

• The products and services you own are in production, used by real teams, and operate with clear…