Experience:

• 8+ years of experience
• Over 3 years of experience in developing and scaling Generative AI projects from prototypes to enterprise production

Qualification:

• Bachelor's Degree in computer science, Data Science, or a related field

Role Focus:

• Architect end-to-end enterprise Generative AI solutions
• Define and enforce agentic design standards across teams
• Align technology choices with clients’ cloud platforms and infrastructure
• Collaborate with business stakeholders to translate objectives into AI requirements
• Establish observability, testing, and operational standards for AI solutions
• Lead and mentor GenAI/Agentic AI engineering teams
• Evaluate, select, and implement agentic AI technology stacks

Additional responsibilities:

• Take ownership of projects including planning, budgeting, execution, and completion
• Partner with team leadership to ensure quality, timelines, and deliverables
• Develop skills outside comfort zone and encourage others
• Mentor others and deepen team expertise through work reviews
• Address conflicts and engage in difficult conversations with clients and stakeholders
• Uphold professional and technical standards, code of conduct, and independence requirements
• Participate in dynamic and digitally enabled training to grow technical and professional skills

Nice to have:

• Experience implementing AI interoperability protocols like MCP and A2A at scale
• Skilled in enterprise cloud AI platforms such as Azure AI Foundry, Amazon Bedrock, Google Vertex AI
• Relevant AI or solution architecture certifications

More skills:

Generative AI, agentic system designs, multi-agent orchestration, autonomous task execution, tool-use chains, LLM integration, agent communication protocols, intelligent task routing, lifecycle management, shared tool registries, orchestration frameworks (LangGraph, CrewAI, AutoGen, Semantic Kernel Agents), cloud platforms and infrastructure, telemetry, monitoring, automated regression tests, simulation environments, production SLAs, vector databases (Pinecone, Weaviate, Azure AI Search), observability tools (LangSmith, Langfuse, Arize AI), AI-powered development tools, DevOps, containerized architectures, CI/CD pipelines (Azure DevOps, GitHub Actions), Python programming, Retrieval Augmented Generation (RAG) architectures, AI/ML fundamentals, LLM security risks and defense-in-depth safeguards, containerization, cloud-native orchestration (Kubernetes, Docker, serverless), event-driven architectures

Other:

• Work within PwC Acceleration Centers supporting Advisory, Assurance, Tax and Business Services
• Engage in challenging projects providing distinctive services to support client engagements
• Lead with integrity and authenticity, articulating PwC's purpose and values
• Embrace technology and innovation to enhance delivery and encourage others