AI Governance Engineering Lead

Janus Henderson•Denver, CO

4d•Hybrid

About The Position

This is an engineering role within AI Technology, reporting to the Head of AI Technology. The company is undergoing an AI transformation and requires an engineer to build governance into the AI platform. This role involves translating requirements from risk, legal, privacy, and audit specialists into technical designs and implementing them on the Nexus and Accio platforms. The focus is on building controls as platform capabilities rather than documentation, ensuring engineers can satisfy them through standard paths, and generating evidence for assurance. Success means production AI workloads have defined ownership, risk classification, evaluation records, approved access, telemetry, and release evidence, with a proportionate lifecycle for different AI deployments.

Requirements

At least six years in software, platform, or security engineering, with a track record of building and operating things that reached production.
Strong Python and SQL.
Hands-on ability with APIs, infrastructure as code, and CI/CD.
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.
Clear communication — you can write a technical standard an engineer can implement, and explain to a non-engineer why the platform does what it does.

Nice To Haves

Policy-as-code tooling such as Open Policy Agent or Rego, and automated evidence or compliance-as-code pipelines.
Entra ID, Microsoft Purview, DLP policy design, or data classification across a Microsoft 365 estate.
Experience securing or governing agents, tool execution, MCP servers, or other machine-to-machine interfaces.
Experience building internal developer platforms, golden-path patterns, or self-service guardrails used by other engineering teams.
Snowflake, Microsoft Fabric / OneLake, and governed enterprise data access patterns.
Exposure to a regulated environment, or to Internal Audit and independent control testing.

Responsibilities

Build governance into the platform by turning policies, standards, and risk decisions into reusable controls, policy-as-code, deployment gates, and secure defaults.
Create self-service governance patterns and templates for approved teams to build safely without repeated manual approvals.
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 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 for each tier.
Engineer identity, access, and permissions by designing and implementing 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 approval and human-in-the-loop patterns for high-stakes actions, while keeping low-risk activity self-service.
Implement an auditable framework for agents and end-user-developed applications, covering ownership, permissions, data, testing, change history, and retirement.
Build the evidence, telemetry, and evaluation layer by defining and building 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 dashboards and evidence packs for service owners, Risk, Infosec, and Internal Audit to use directly.
Translate across domains by working with Risk’s AI governance specialist, Infosec, Legal, Compliance, Privacy, Records Management, and TPRM to understand needs and convert them into technical requirements.
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 applicable controls.
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.
Work alongside Percepta so controls and operating knowledge transfer into ownership.

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.
Competitive compensation
Pension/retirement plans
Various health, wellbeing and lifestyle benefits