6 days ago
Responsibilities
- Architect and deliver secure, governed, transparent, resilient AI, GenAI, and agentic systems end to end.
- Develop Trust by Design reference architectures covering guardrails, content safety, prompt hardening, auditability, privacy, encryption, identity, and human escalation.
- Translate regulatory, policy, privacy, ethical, data-governance, and model-risk requirements into production technical controls.
- Lead AI assurance strategies covering functional, safety, robustness, privacy, explainability, monitoring, validation, and control effectiveness testing.
- Address AI security risks including threat modeling, prompt injection, adversarial testing, jailbreaks, and data exfiltration.
- Act as technical delivery lead and solution architect for major client engagements, owning architecture decisions, quality, and outcomes.
- Lead multidisciplinary teams across Responsible AI, engineering, cyber, data governance, and risk; mentor and upskill practitioners.
- Create reusable frameworks, playbooks, accelerators, and reference architectures, and contribute to go-to-market and thought leadership.
Requirements
- Deep expertise in Responsible AI principles and governance or control frameworks aligned with standards such as NIST AI RMF and ISO/IEC 42001.
- Strong understanding of the UK and EU AI regulatory landscape, including the EU AI Act, data protection, model risk, and AI ethics.
- Proven experience designing and implementing enterprise-grade AI systems as a solution or technical architect.
- Strong understanding of GenAI architectures including RAG, tool use, function calling, agents, orchestration, failure modes, and risk controls.
- Hands-on or architecture-level experience with cloud AI platforms, preferably Azure and AWS, plus data platforms, API management, and identity/access patterns.
- Familiarity with vector databases, embedding pipelines, feature stores, model registries, prompt and trace observability, and CI/CD for ML or LLM systems.
- Experience designing AI testing and validation approaches, including safety testing, adversarial testing or red teaming, monitoring, and incident management.
- Working knowledge of fine-tuning, parameter-efficient approaches, evaluation harnesses, and risk or quality measurement.
- Experience in consulting or industry leading complex AI, data, analytics, or model-risk initiatives.
- Ability to influence executives and risk leaders and translate technical issues into business and regulatory implications.
- Commercial experience shaping proposals, leading workstreams, and supporting large engagements with Partners.
- Preferred qualifications include model governance or MRM platforms, GenAI guardrail tools, LLMOps and observability tooling, AI security programs, external Responsible AI thought leadership, and relevant certifications or standards-body contributions.
Benefits
- Flexible working split between office, home, and client site.
- Private medical cover and 24/7 access to a qualified virtual GP.
- Six volunteering days per year and additional benefits designed to support and reward employees.
- Visa sponsorship is available; government clearance is not required.
- Applications close June 5, 2026, and the posting lists a September 4, 2026 end date.
About PwC
At PwC, we help clients drive their companies to the leading edge. We’re a tech-forward, people-empowered network with more than 370,000 people in 149 countries. Across audit and assurance, tax and legal, deals and consulting we help build, accelerate and sustain momentum. Find out more at www.pwc.com. PwC: Audit and assurance, consulting and tax services PwC refers to the PwC network and/or one or more of its member firms, each of which is a separate legal entity. Content on this page has been prepared for general information only and is not intended to be relied upon as accounting, tax or professional advice. Please reach out to your advisors for specific advice.