Senior AI Architect

PwC is a global network of more than 370,000 professionals in 149 countries that turns challenges into opportunities. We create innovative solutions in audit, consulting, tax and technology, combining knowledge from all over the world.

We are seeking an AI Architect to design, build, and guide the secure and scalable adoption of AI platforms and AI‑driven applications. This role partners with engineering, data science, and product teams to define AI solution architectures, ensure technical excellence, and embed best practices throughout the AI lifecycle—from data ingestion and model development to deployment and monitoring.

Key Responsibilities:

AI Architecture & Design

• Architect scalable AI/ML and LLM‑based solutions, including data flows, integration patterns, and deployment approaches.
• Conduct architectural reviews for new AI features and system changes.
• Define reference architectures and reusable AI patterns.

Collaboration With Engineering & Product Teams

• Partner with engineering, MLOps, and product teams to translate needs into AI solutions.
• Provide technical guidance that balances performance, cost, and speed.
• Build repeatable processes for reviewing AI capabilities and changes.

MLOps & Deployment

• Support integration of AI workflows into CI/CD processes.
• Promote automated testing, validation, and monitoring of AI models.
• Collaborate on tooling for model deployment, versioning, and observability.

Governance & Responsible AI

• Ensure AI designs follow internal governance and responsible AI principles.
• Support documentation and transparency for AI system behaviors.
• Align architectures with regulatory and compliance requirements.

Monitoring & Continuous Improvement

• Guide teams on monitoring, anomaly detection, and model performance tracking.
• Identify improvement opportunities and evolve AI architecture standards.
• Share best practices and mentor teams on modern AI technologies.

Required Skills:

• Experience in AI/ML system design, cloud‑native architecture, or application architecture.
• Strong understanding of the AI/ML development lifecycle, including training, deployment, and inference.
• Hands‑on exposure to LLM applications, RAG pipelines, vector databases, and API‑based AI integrations.
• Familiarity with MLOps, DevOps, and modern cloud platforms (Azure, AWS, GCP).
• Strong communication skills and ability to work cross‑functionally.
• Curiosity and passion for emerging AI technologies.

Preferred Qualifications:

• Experience building or securing generative AI applications.
• Knowledge of frameworks like NIST AI RMF, OWASP LLM Top 10, MITRE ATLAS, ISO/IEC 42001.
• Cloud or AI‑related certifications.
• Background in ML engineering or MLOps.

Policy statements:
https://www.pwc.com/ua/uk/about/privacy.html