- Company Name
- PwC UK
- Job Title
- Senior Manager, Responsible AI Solution Architect
- Job Description
-
**Job title**: Senior Manager, Responsible AI Solution Architect
**Role Summary**: Lead design and delivery of end‑to‑end Responsible AI solutions for GenAI and emerging agentic platforms. Translate Responsible AI principles, regulatory, privacy and ethical requirements into secure, governed, and observable architectures that meet enterprise and regulatory standards.
**Expectations**:
- Deliver production‑ready AI architectures that embed “Trust by Design” patterns.
- Translate UK/EU AI Act, NIST AI RMF, ISO/IEC 42001, and data protection rules into concrete technical controls across the AI lifecycle.
- Influence large organisations in adopting safe, compliant AI through technical leadership and scalable governance.
**Key Responsibilities**:
1. Architect end‑to‑end AI solutions (data, identity, model integration, orchestration, deployment, monitoring, incident response).
2. Develop and evolve Trust by Design reference architectures for GenAI/agentic AI, incorporating safety guardrails, transparency, auditability, privacy, security, and human‑in‑the‑loop mechanisms.
3. Translate regulatory, policy and ethical requirements into secure‑by‑design SDLC practices and model‑life‑cycle controls.
4. Partner with cyber & resilience teams to advance threat modeling, prompt‑injection/ data‑exfiltration mitigations, adversarial testing, and assurance frameworks.
5. Define and lead AI assurance strategies for testing, validation, monitoring, and control effectiveness across classical ML and GenAI.
**Required Skills**:
- Deep knowledge of Responsible AI frameworks (NIST AI RMF, ISO/IEC 42001).
- Strong grasp of UK/EU AI Act, GDPR, model risk and AI ethics.
- Proven experience as a solution/technical architect delivering enterprise‑grade AI systems.
- Expertise in GenAI architectures (RAG, agent orchestration, function calling) and awareness of failure modes & risk controls.
- Hands‑on or architecture‑level experience with Azure AI, AWS Bedrock/SageMaker, and related cloud services (AI/ML, IAM/KMS, monitoring, data governance).
- Familiarity with AI ecosystem tooling: vector databases, embedding pipelines, feature stores, model registries, prompt/trace observability, CI/CD for ML/LLM.
- Demonstrated ability to design testing, validation, adversarial testing, monitoring, and incident‑management processes.
- Working knowledge of fine‑tuning methods, evaluation harnesses, risk/quality measurement.
**Required Education & Certifications**:
- Bachelor’s degree in Computer Science, Engineering, Data Science or related field (Master’s preferred).
- 7+ years of relevant experience in AI/ML architecture and solution delivery.
- Certifications such as Azure AI Engineer Associate, AWS Certified Machine Learning – Specialty, or ISO/IEC 42001 Lead Implementer are highly desirable.