Janus Henderson Investors on cord

Janus Henderson Investors

AI Governance Engineering Lead

External position
London, UK
Hiring internally for Janus Henderson Investors?
Finance · Investment
We’re a global asset manager dedicated to investing in a #BrighterFutureTogether for our clients.
Posted
a week ago
Checked
cord regularly checks that external positions are still open
2 days ago

Skills & Experience

Job roles: AI Engineer
Experience level: Lead
Core skills considered: Python, SQL, APIs
Other skills considered: CI/CD, Cloud Computing, Azure

Logistics

Base salary: Undisclosed
Some companies on cord are unable to disclose salaries publicly due to internal company policies. Message the company for salary information.
Employment type: Permanent
Remote working: Hybrid (up to 2 remote days p/w)
Visa sponsorship: Not available

Job Description

This is an engineering role. 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 inside boundaries that actually hold. Your job is to make those boundaries part of the platform - governance as code and by design, so that engineers and users inherit the right behaviour automatically instead of passing through a review queue at the end.

You will sit within AI Technology and report to the Head of AI Technology. You will not be the firm's expert on AI regulation, and you do not need to be: Risk has a dedicated AI governance specialist who owns regulatory interpretation, policy, and standards, and Infosec owns security policy and security-control approval. You will work with both, day to day. What we need from you is the engineering half of that partnership - the person who can take what a risk, legal, privacy, or audit specialist tells them they need, work out what it means in a system, and build it.

The controls you build land on our two central platforms: Nexus, our agentic workspace, where employees and citizen developers build and run AI applications, agents, and shared skills; and Accio, our centralised MCP server, which consumes other MCP servers and presents enterprise datasets through one governed interface. In practice that means identity and permissions for agents and tools, policy-as-code and deployment gates, evaluation hooks in the release path, and the telemetry and evidence that show any of it is working - across the model gateway, agent orchestration, and the applications built on top.

The skill that decides whether this role succeeds is translation. You will sit with people whose domains are nothing like yours, understand what they are actually asking for rather than the words they used, and turn it into a technical design they recognise as their requirement. You should be able to hit the ground running on identity, cloud, and controls, and be comfortable that the AI part of the problem is changing faster than anyone's standards for it.


What success looks like

  • Controls exist as working platform capability rather than documents. Engineers satisfy them through standard paths, without informal interpretation or repeated meetings.
  • Risk, Infosec, and Internal Audit recognise their requirements in what you built, and can test control operation from evidence the platform generates rather than assembled after the event.
  • Every production AI workload has a named owner, risk classification, evaluation record, approved access, operating telemetry, and retrievable release evidence.
  • Low-risk model and software updates move through a repeatable, time-bound path while higher-risk deployments get the scrutiny they require, and when a control fails the lesson lands in a platform default rather than a report.

Your responsibilities


Build governance into the platform

  • Turn the policies, standards, and risk decisions that Risk and Infosec own into reusable controls, policy-as-code, deployment gates, and secure defaults.
  • Create self-service governance patterns and templates so approved teams can build safely without repeated manual approvals, and embed control checks and evidence capture into repositories, CI/CD pipelines, infrastructure-as-code, and deployment workflows.
  • Establish cost, usage, data-access, and model-access boundaries that are enforced by default through the model gateway and platform services.
  • Define a proportionate lifecycle for experiments, pilots, production AI products, model changes, and autonomous agents, and set the release requirements that go with each tier.

Engineer identity, access, and permissions

  • Design and implement identity, authentication, authorisation, and permission patterns for agents, models, tools, connectors, and service accounts, working with enterprise IAM and AI Security.
  • Implement least privilege and entitlement models that hold when a request crosses several systems, including through Accio to downstream MCP servers.
  • Build the approval and human-in-the-loop patterns that high-stakes actions require, while keeping low-risk activity self-service.
  • Implement an auditable framework for agents and end-user-developed applications, covering named ownership, permissions, approved data, testing, change history, and retirement.

Build the evidence, telemetry, and evaluation layer

  • Define and build the event and evidence model needed to reconstruct prompts, model responses, tool calls, agent decisions, approvals, data access, and cost.
  • Work with AI Engineering and AI Platforms to make telemetry consistent across the model gateway, agent orchestration, applications, and external providers.
  • Build evaluation and regression hooks into the release path, with acceptance thresholds for models, prompts, agents, and platform changes, automated wherever practical.
  • Design monitoring for control failures, model drift, anomalous use, permission breaches, and high-risk actions, with clear escalation and remediation paths.
  • Build the dashboards and evidence packs that service owners, Risk, Infosec, and Internal Audit use directly, so assurance does not depend on you being in the room.

Translate across domains, and work across the firm

  • Work with Risk's AI governance specialist, Infosec, Legal, Compliance, Privacy, Records Management, and TPRM to understand what each needs, and convert it into technical requirements engineers can implement.
  • Write standards and control requirements that are specific enough to build from, and explain back to non-engineers how the platform behaves and why.
  • Advise AI Architecture, AI Engineering, AI Platforms, and Forward Deployed Engineering on control design, and help teams classify use cases and understand which controls apply before they build.
  • Support risk-based onboarding of new foundation models, AI software, and connectors with AI Platforms and AI Security without restarting the process for every low-risk update, and work alongside Percepta so controls and operating knowledge transfer into our ownership.

Must have skills

  • At least six years in software, platform, or security engineering, with a track record of building and operating things that reached production. This is an engineering role - a policy, audit, or compliance background is not what we are looking for.
  • Strong Python and SQL, and hands-on ability with APIs, infrastructure as code, and CI/CD. You will build the controls, not specify them for somebody else to build.
  • Real depth in identity and access: authentication, authorisation, RBAC, service principals and workload identity, secrets management, entitlement models, and least privilege.
  • A practical understanding of what a technical control is and how to implement one - preventive and detective controls, secure defaults, deployment gates, and the evidence a control has to produce.
  • Hands-on experience with a major cloud, ideally Azure, including logging, monitoring, and data-protection primitives.
  • The ability to work with stakeholders whose domain is not yours - risk, legal, privacy, compliance, audit, security - understand what they actually need rather than the words they used, and turn it into a technical design they recognise as their requirement.
  • Practical knowledge of generative AI and agentic systems: foundation models, prompts, retrieval, tools, connectors, model gateways, and autonomous workflows.
  • Judgement to distinguish a control objective from a preferred implementation and apply proportionate controls based on actual risk, and clear communication - you can write a technical standard an engineer can implement

Company Benefits

  • Hybrid working and reasonable accommodations
  • Generous Holiday policies
  • 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
  • All-inclusive approach to Diversity, Equity and Inclusion
  • Maternal/paternal leave benefits and family services
  • Complimentary subscription to Headspace – the mindfulness app
  • Corporate membership to ClassPass and other health and well-being benefits
  • Unique employee events and programs including a 14er challenge
  • Complimentary beverages, snacks and all employee Happy Hours
AI Governance Engineering Lead at Janus Henderson Investors
Position posted a week ago

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Starling Bank on cord

Starling Bank

Full Stack Engineer (ML Ops)

London, UK
FinTech · Banking · Finance
A better bank for everyone
Active
over 6 months ago
Responds to
0% of requests
Responds in
1h 55m
Requests
7 pending

Skills & Experience

Job roles: Full Stack
Experience level: Mid, Senior
Core skills considered: Java, React, Redux, AWS, JavaScript

Logistics

Base salary: £70K - £110K
Employment type: Permanent
Remote working: Hybrid (up to 2 remote days p/w)
Visa sponsorship: Not available

Job Description

Starling is the UK’s first and leading digital bank on a mission to fix banking! Our vision is fast technology, fair service, and honest values. All at the tap of a phone, all the time.

Starling is the UK’s first and leading digital bank on a mission to fix banking! We built a new kind of bank because we knew technology had the power to help people save, spend and manage their money in a new and transformative way.

We’re a fully licensed UK bank with the culture and spirit of a fast-moving, disruptive tech company. We’re a bank, but better: fairer, easier to use and designed to demystify money for everyone. We employ more than 3,000 people across our London, Southampton, Cardiff and Manchester offices.

Our technologists are at the very heart of Starling and enjoy working in a fast-paced environment that is all about building things, creating new stuff, and disruptive technology that keeps us on the cutting edge of fintech. We operate a flat structure to empower you to make decisions regardless of what your primary responsibilities may be, innovation and collaboration will be at the core of everything you do. Help is never far away in our open culture, you will find support in your team and from across the business, we are in this together!

The way to thrive and shine within Starling is to be a self-driven individual and be able to take full ownership of everything around you: From building things, designing, discovering, to sharing knowledge with your colleagues and making sure all processes are efficient and productive to deliver the best possible results for our customers. Our purpose is underpinned by five Starling values: Listen, Keep It Simple, Do The Right Thing, Own It, and Aim For Greatness.

Hybrid Working

We have a Hybrid approach to working here at Starling - our preference is that you're located within a commutable distance of one of our offices so that we're able to interact and collaborate in person. We don't like to mandate how much you visit the office and work from home, that's to be agreed upon between you and your manager.

Our Data Environment

Our Data teams are excited about the value of data within the business, powers our product decisions to improve things for our customers and enhance effective and agile decision making, regardless of what their primary tech stack may be. Hear from the team in our latest blogs or our case studies with Women in Tech.

We are looking for talented data professionals at all levels to join the team. We value people being engaged and caring about customers, caring about the code they write and the contribution they make to Starling. People with a broad ability to apply themselves to a multitude of problems and challenges, who can work across teams do great things here at Starling, to continue changing banking for good.

Requirements

We have built our entire banking platform in house and mostly in Java. We are looking for people who want to work on building the tooling that is used by our engineers on a daily basis.

We are looking for people who are truly full stack, and are as comfortable polishing their javascript front end as they are debugging the innards of their java applications database interactions, or standing up infrastructure with terraform. We are looking for people who can:

  • Design REST apis.
  • Code backend services, ideally using Java, or another other server side compiled language.
  • Develop modern front ends, ideally using React and Redux.
  • Get their code into the cloud and support it there, ideally on AWS.
  • Believe in clean coding, simple solutions, automated testing and continuous deployment.
  • Like to take ownership of a feature from the original idea through to live.
  • Think (like us) that a small number of empowered developers is the right way to deliver software.

Company Benefits

  • 33 days holiday (including flexible bank holidays)
  • An extra day’s holiday for your birthday
  • 16 hours paid volunteering time a year
  • Part-time and/or flexible hours available for most roles
  • Salary sacrifice, company enhanced pension scheme
  • Life insurance at 4x your salary
  • Hybrid/remote working
  • Private Medical Insurance with VitalityHealth including mental health support and cancer care. Partner benefits include discounts with Waitrose, Mr&Mrs Smith and Peloton
  • Generous family-friendly policies
  • Varied social groups set up and run by our employees
  • Perkbox membership giving access to retail discounts, a wellness platform for physical and mental health, and weekly free and boosted perks
  • Access to initiatives like Cycle to Work, Salary Sacrificed Gym partnerships and Electric Vehicle (EV) leasing

Full details are available on our careers site

Interview Process

Interviewing is a two way process and we want you to have the time and opportunity to get to know us, as much as we are getting to know you! Our interviews are conversational and we want to get the best from you, so come with questions and be curious. In general you can expect the below, following a chat with one of our Talent Team:

  • Stage 1 - 30 mins with one of the team
  • Stage 2 - Take home challenge
  • Stage 3 - 90 mins technical interview with two team members
  • Stage 3 - 45 min final with an executive and a member of the people team
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