Senior AI Engineer

Why work for us

A career at Janus Henderson is more than a job its 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. 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 teams 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 Perceptas 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 Teams 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.

What success looks like

• The products and services you own are in production used by real teams and operate with clear ownership telemetry and evaluation results.
• What you build gets reused. Other engineers agents and applications consume it through Accio or as a skill tool or connector on Nexus rather than building their own.
• Platforms built jointly with Percepta transfer into our ownership with maintainable designs and a team that can extend them without external help.
• Evaluation observability and control are built into what you ship rather than bolted on before release.

Your responsibilities

Build and run our AI products and platform

• Design build and productionise AI products and shared platform services taking a workstream end to end and owning it through to live running.
• Build for reuse turning capability proven in one product into shared components libraries skills tools MCP servers and connectors.
• Implement infrastructure as code own CI/CD pipelines and accept services into operation only when ownership controls and support are clear.
• Investigate incidents and defects in the services you own lead recovery carry fixes through to the underlying cause and act as L3 escalation.

Engineer agents orchestration and the application layer

• Build agentic applications and workflows covering agent design prompt and context engineering tool use memory retrieval and human-in-the-loop controls.
• Implement model selection routing and fallback through the model gateway handling provider change without hiding differences in capability cost or behaviour.
• Build the orchestration layer that long-running and multi-step agents depend on covering permissions workload isolation safe execution and the applications built on it.
• Test the claims made for new models frameworks and patterns before recommending we adopt them.

Make enterprise data AI-ready

• Build governed AI-ready views indexes semantic context and connectors over Snowflake enterprise platforms APIs and external providers.
• Extend Accio so new datasets and downstream MCP servers are reachable through one governed interface rather than one-off integrations.
• Build ingestion pipelines and data models where source data does not arrive usable while canonical source ownership stays with the relevant Technology team.
• Own lineage quality and freshness for the data your products depend on and implement least-privilege access for users agents tools and service identities.

Build business-area applications and decommission SaaS

• Own the end-to-end build of targeted business applications on the AI stack Distribution first then areas such as trading investment risk client servicing and operations delivered for a named business owner rather than for every team at once.
• Drive SaaS decommissioning: where a bought subscription can be replaced by an in-house build own the delivery of that replacement end-to-end see the displaced product retired and work with Procurement and Finance to consolidate the licence.
• Prioritise the builds where in-house ownership gives the firm more control lower cost or capability no vendor sells and reuse existing Accio datasets skills and connectors instead of rebuilding them per application.
• Take each application through the same evaluation controls and release evidence as the shared products and own its support and lifecycle once live or hand it to a clear owner.

Build in evaluation and control and work with the team

• Build evaluation and regression suites for models prompts agents and platform changes meet the agreed thresholds before release and instrument what you build for quality safety reliability latency drift usage and cost.
• Implement the controls defined by AI Governance Implementation and AI Security as code and secure defaults and produce release evidence proportionate to the risk of the use case generated by the platform rather than assembled after the event.
• Work alongside Percepta engineers on Libros PRISM and the wider estate holding joint work to our engineering standards and raising maintainability problems while they are still cheap to fix.
• Mentor AI Engineers through pairing design discussion and code review and help establish the teams engineering standards agentic SDLC and definition of done.
• Work with AI Architecture to turn reference patterns into implementations teams use partner with Forward Deployed Engineering so proven solutions become supported shared capability and feed adoption data from the AI Enablement Partners into the backlog.

Must have skills

• At least six years in software data or platform engineering with a track record of shipping and operating production systems rather than prototypes.
• Production experience with LLM applications and agentic systems covering prompt and context engineering agent development retrieval tool use evaluation and deployment at scale.
• Strong Python and SQL with the judgement to write code others can maintain and extend.
• Hands-on experience building agentic capability such as MCP servers tools skills or connectors for other systems and agents to consume.
• Hands-on experience with a major cloud ideally Azure including containers or serverless compute infrastructure as code CI/CD identity RBAC and secret management.
• Experience owning services in production monitoring incident investigation upgrades lifecycle management and establishing evaluation and observability for AI systems.
• Good judgement in a regulated environment translating security privacy risk and audit requirements into working technical controls.
• Experience mentoring engineers and leading technical work without relying on reporting authority and clear communication with engineers control functions and business stakeholders.

Nice to have skills

• Asset management or financial services domain knowledge particularly the investment process distribution or front-office workflows.
• Azure AI Foundry Azure OpenAI Anthropic Claude model gateways inference routing or agent orchestration platforms.
• Snowflake Microsoft Fabric / OneLake or comparable governed enterprise data platforms.
• TypeScript or a second production language and front-end experience for user-facing AI applications.
• Experience building internal developer platforms or golden-path patterns used by other engineering teams or taking partner-built software into internal ownership.

What to expect when you join our firm

• 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

Supervisory responsibilities

• No. This is a senior individual-contributor role. The Senior Applied AI Engineer leads technical delivery sets implementation standards and mentors AI Engineers but does not line-manage. The role may act as technical lead for a product or platform workstream.

Compensation information

The base salary range for this position is $130000 - $220000. This range is estimated for this role. Actual pay may be different. This position will be open through October 31 2026.

Colorado law requires an estimated closing date for job postings. Please dont be discouraged from applying if you see this date has passed.

At Janus Henderson Investors were committed to an inclusive and supportive environment. We believe diversity improves results and we welcome applications from candidates from all backgrounds. Dont worry if you dont think you tick every box we still want to hear from you! We understand everyone has different commitments and while we cant accommodate every flexible working request were happy to be asked about work flexibility and our hybrid working environment. If you need any reasonable accommodations during our recruitment process please get in touch and let us know at .

#LI-LN2 #LI-Hybrid

Annual Bonus Opportunity: Position may be eligible to receive an annual discretionary bonus award from the profit pool. The profit pool is funded based on Company profits. Individual bonuses are determined based on Company department team and individual performance.

Benefits: Janus Henderson is committed to offering a comprehensive total rewards package to eligible employees that includes; competitive compensation pension/retirement plans and various health wellbeing and lifestyle benefits. To learn more about our offerings please visit the Why Join Us section on the career pagehere.

Janus Henderson Investors is an equal opportunity employer .All qualified applicants will receive consideration for employment without regard to race color religion sex sexual orientation gender identity national origin disability or veteran status. All applications are subject to background checks.

Janus Henderson (including its subsidiaries) will not maintain existing or sponsor new industry registrations or licenses where not supported by an employees job functions (as determined by Janus Henderson at its sole discretion).

You should be willing to adhere to the provisions of our Investment Advisory Code of Ethics related to personal securities activities and other disclosure and certification requirements including past political contributions and political activities. Applicants past political contributions or activity may impact applicants eligibility for this position.

You will be expected to understand the regulatory obligations of the firm and abide by the regulated entity requirements and JHI policies applicable for your role.

Required Experience:

Senior IC