This position sits at the intersection of enterprise strategy, technical innovation, and risk architecture. It is designed for an engineering-minded strategist or a risk professional who thrives on architecting safeguards for complex technological ecosystems.
You will work at the cutting edge of modern enterprise infrastructure—spanning
Agentic AI risk frameworks, AI sovereignty, decentralized model routing, and the deployment of autonomous enterprise worker fleets
.
Your mission is to bridge the gap between rapid machine learning innovation and ironclad operational trust, ensuring that advanced AI assets remain safe, transparent, and completely aligned with global regulatory frameworks.
Core Responsibilities
* Architect Enterprise AI Guardrails:
Design, implement, and continuously enhance end-to-end AI assurance frameworks. You will directly address model-specific risks including fairness, bias, transparency, systemic privacy, and adversarial security.
* Execute Advanced Risk Appraisals:
Lead formal AI risk, impact, and control assessments. You will evaluate complex autonomous systems for operational, ethical, legal, and societal vulnerabilities, particularly within highly scrutinized or heavily regulated environments.
* Embed First-Line Governance:
Standardize risk management workflows directly into the machine learning lifecycle (1st line of assurance). This covers everything from initial use-case selection and architectural design to active testing, CI/CD deployment, continuous monitoring, and eventual model retirement.
* Orchestrate Cross-Functional Trust:
Act as the strategic anchor between product engineering, data science, cybersecurity, legal, and compliance divisions. Ensure all deployed solutions operate strictly within organizational risk appetites and shifting regulatory expectations.
* Enforce Runtime Performance \& Telemetry:
Define precise operational requirements for continuous telemetry, drift detection, prompt-injection defence, automated incident management, and post-deployment validation.
Technical Profile \& Tooling Expertise
We are seeking a professional who understands both the theory of AI compliance and the practical tooling required to enforce it. You should have familiarity with, or a strong desire to master, the following enterprise infrastructure ecosystems:
* Cloud-Native AI Control Planes \& Infrastructure Gateways:
Exposure to native hyperscaler governance environments, including
AWS AgentCore, Amazon Bedrock Guardrails, AWS Security Hub, Azure Foundry Control Plane, Microsoft Agent 365
, and Azure API Management.
* Independent LLM Gateways \& Traffic Routers:
Familiarity with proxy and orchestration routing tools such as
Portkey, Fiddler AI, Speakeasy, LiteLLM, Zuplo, Kong AI Gateway, or Cloudflare AI Gateway
.
* Agentic Orchestration \& Compliance Management:
Understanding of decentralized agent-to-tool networking protocols, Model Context Protocol (MCP) authentication, and governance platforms like
Xnode Cortx, Exemplar, TrueFoundry, or xpander
.
Required Skills \& Experience
* AI Lifecycle Governance:
Proven experience embedding concrete risk management gates across complex machine learning workflows, from development sandboxes to live production environments.
* Risk \& Control Evaluations:
Demonstrable track record of executing thorough AI risk assessments, data privacy impact assessments (DPIAs), or technical assurance reviews.
* Technical Translation:
Outstanding communication skills with a proven ability to translate abstract regulatory demands or complex model behaviors into pragmatic, actionable recommendations for C-suite and engineering stakeholders alike.
* Monitoring \& Observability:
Strong knowledge of post-deployment assurance practices, model drift tracking, explainable AI (XAI) metrics, and automated system override protocols.
Desirable Experience \& Qualifications
* Cross-Industry Versatility:
Experience deploying or auditing AI systems across diverse fields, including the
Public Sector (e.g., Central Government and Defence)
or commercial industries like
Financial Services, Life Sciences, Automotive, and Manufacturing
.
* Industry Certifications (Highly Valued):
* *Governance \& Strategy:*
IAPP Certified Artificial Intelligence Governance Professional (AIGP)
or Lead AI Risk Manager (
ISO/IEC 42001
).
* *Risk \& Security Management:*
ISACA Advanced in AI Security Management (AAISM)
or
Advanced in AI Risk (AAIR)
.
* *Cloud/Technical Architecture:*
Azure AI DevOps \& GenAIOps Engineer (AI-300)
,
Azure AI Engineer Associate
,
AWS Certified Machine Learning Engineer
, or
AWS Security Specialty
.
Personal Attributes
You are a passionate advocate for the safe, responsible, and scalable adoption of emerging technologies. You approach problem-solving with a balanced, pragmatic mindset—understanding how to mitigate risk without suffocating product innovation. You remain calm, structured, and highly effective when navigating ambiguous, high-pressure environments, and you possess an insatiable curiosity for how the AI landscape is evolving.
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