Senior Solutions Architect managing pre - sales technical scoping and customer solutions for Amazon Connect. Collaborating with the Contact Center Platform Architecture team to serve unique business needs.
About the role
- Senior Manager and Responsible AI Solution Architect at PwC shaping Responsible AI and leading trusted AI solution architecture across UK sectors.
Responsibilities
- shape and deliver PwC’s Responsible AI, Ethics, Security and Trust agenda
- lead the architecture and delivery of trusted AI solutions across GenAI and agentic platforms
- help clients move from principles to production by designing secure, governed and observable AI systems
- lead the design and delivery of trusted, secure and compliant AI systems across GenAI and emerging agentic platforms
- translate Responsible AI principles and regulatory requirements into production ready architectures
- architect end-to-end AI / GenAI / agentic solutions (from data and identity through model integration, orchestration, deployment, monitoring and incident response)
- develop and mature PwC’s “Trust by Design” reference architectures and patterns for GenAI and agentic AI
- translate regulatory, policy, privacy and ethical requirements into concrete technical controls embedded across
Requirements
- Deep expertise in Responsible AI principles and operating models, including design or assessment of governance/control frameworks aligned to recognised standards (e.g., NIST AI RMF, ISO/IEC 42001)
- Strong understanding of UK/EU AI regulatory landscape (including EU AI Act), data protection, model risk concepts, and AI ethics
- Proven experience as a solution architect / technical architect designing and implementing enterprise-grade AI systems
- Strong understanding of GenAI architectures (RAG, tool use, function calling, agents, orchestration patterns), including failure modes and risk controls
- Hands-on or architecture-level experience with cloud AI platforms and services, ideally across Azure (e.g., Azure AI / Azure OpenAI, Prompt Flow, AML, Purview, Sentinel), AWS (e.g., Bedrock, SageMaker, IAM/KMS, CloudWatch), and other common data platforms, API management, and identity/access patterns
- Familiarity with AI enabling technologies and ecosystems: vector databases, embedding pipelines, feature stores, model registries, prompt/trace observability, CI/CD for ML/LLM systems
- Demonstrated ability to design and lead testing and validation approaches for AI systems, including GenAI safety testing, adversarial testing/red teaming, monitoring and incident management
- Working knowledge of emerging methods such as fine-tuning (e.g. parameter-efficient approaches), evaluation harnesses, and measurement of risk/quality
Benefits
- empowered flexibility and a working week split between office, home and client site
- private medical cover and 24/7 access to a qualified virtual GP
- six volunteering days a year and much more
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
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