Principal Forward Deployed Engineer

Janus Henderson Investors•Denver, CO

6d•$195,000 - $225,000•Hybrid

About The Position

This is a hands-on engineering leadership role. You will build, and you will lead the people who build. It starts with your own hands on the keyboard; it grows into ownership of a team, its deliverables, and the roadmap they work to. 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 Forward Deployed Engineering is the part of it that embeds with the business and builds what business units cannot stand up alone. As Principal Forward Deployed Engineer you are the most senior engineer in that team and its lead. Reporting to the Head of AI Technology, you set the technical bar, own the team’s deliverables and outputs, and are accountable for what it ships and runs — while still embedding with business units yourself. You will also form part of the AI Technical Leadership Team, whose remit is to build an AI Technology roadmap that lines up with the JHI strategic roadmap and own the deliverables against it. It works across every AI technology remit — AI Platforms, AI Architecture, AI Engineering, and AI Governance Implementation — keeping them aligned so the firm has one coherent plan rather than four competing ones. It also decides what we adopt: you will review new models, tools, and vendors, test their claims against our own workloads, and judge whether they are feasible here, technically, commercially, and against the constraints a regulated asset manager operates under. The balance of the role will shift, and we would rather be explicit than discover a mismatch later. Today it is predominantly hands-on: you are expected to be one of the strongest builders in the firm. As the team grows, the weight moves towards strategy, roadmap, and management, and your technical contribution shifts from writing most of the code to setting direction and holding the standard. If you want to stay purely hands-on, the Forward Deployed Engineer role is the better fit.

Requirements

At minimum eight years in technical, business-facing engineering roles — forward deployed engineering, solutions engineering, consulting-side software engineering, or engineering embedded in a business unit — including time as the most senior engineer on the work. Former technical founders are encouraged to apply.
Experience leading engineers as a line manager, tech lead, or founder. You need not have run a large team, but you must have been accountable for other people’s delivery.
Strong Python and SQL, and a track record of shipping production applications, with hands-on delivery recent enough to still be real.
Production experience with LLMs — prompt and context engineering, agent development, evaluation, deployment at scale — including agentic capability such as MCP servers, tools, or connectors.
Experience building data pipelines from APIs and enterprise systems, and working knowledge of a major cloud, ideally Azure, with CI/CD, containers, and infrastructure as code.
Experience owning a technical roadmap, and judgement on technology selection — you can evaluate a new tool, model, or vendor, test it properly, and defend the recommendation.
Excellent stakeholder skills, credibility with senior audiences, and the ability to influence without direct authority.
High agency, genuine interest in the business problem, and willingness to move from building towards leading as the team grows.
Experience in a regulated environment where governance, compliance, and data sensitivity shape how solutions are built.

Nice To Haves

Experience standing up a new engineering team or function from scratch, including hiring and defining how it works.
Asset management or financial services domain knowledge, particularly the investment process, front office workflows, or fixed income.
Quantitative investment concepts such as fair value, relative value, signal generation, or portfolio construction.
Snowflake, Microsoft Fabric / OneLake, Azure AI Foundry, model gateways, or AI observability in production.
Vendor selection, commercial negotiation, or licensing at enterprise scale, or contributing to architecture and technology governance forums.

Responsibilities

Lead the team and own its deliverables
Line-manage Forward Deployed Engineers as the team grows: hiring, onboarding, objectives, development, and performance.
Own the team’s deliverables and outputs — what is committed, what is delivered, to what standard, and by when.
Allocate people and effort across the demand pipeline, and be the person who says no, not yet, or not like that.
Hold the engineering bar through design and code review, and grow engineers into owning engagements themselves.
Report progress, risk, and capacity to the Head of AI Technology and to business stakeholders honestly, including when delivery is off track.
Build and deliver, hands on
Design, build, and productionise bespoke, higher-complexity AI solutions yourself, taking the hardest and least-defined engagements personally.
Own the architecture and design decisions for the team’s solutions, keeping them secure, scalable, and aligned to the enterprise core stack.
Take solutions through evaluation, observability, and our AI governance checkpoints, and keep them healthy afterwards.
Own the roadmap and the technology choices
Form part of the AI Technical Leadership Team, and build an AI Technology roadmap that lines up with the JHI strategic roadmap.
Work across the AI technology remits — AI Platforms, AI Architecture, AI Engineering, and AI Governance Implementation — owning the Forward Deployed Engineering deliverables and keeping them aligned to enterprise architecture.
Contribute to AI technology strategy, standards, and buy-versus-build, and to the investment recommendations and backlog that follow.
Review new models, tools, and vendors and determine their feasibility here, weighing cost, licensing, security, supportability, and vendor viability alongside capability, and documenting the recommendation — including the recommendation not to adopt.
Embed with the business and build investment capability
Sit with business users and hold the relationship senior enough that the team is invited into problems early rather than handed finished requirements.
Partner with the AI Enablement Partners on escalated demand, and set realistic expectations with senior stakeholders.
Build advanced investment capability on Nexus, our agentic workspace, taking models and signals from one desk into a supported, firm-wide capability, and lead the build-out of citizen developer workflows through to production.
Expose data and capability through Accio, our centralised MCP server, and as skills, tools, and connectors on Nexus, building reusable components rather than one-off integrations.
Co-build enterprise core-stack deliverables with Percepta and AI Engineering, and represent Forward Deployed Engineering in architecture and design authority forums.

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
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.
competitive compensation
pension/retirement plans
various health, wellbeing and lifestyle benefits