GenAI Lead - Manager

At PwC, our people in data and analytics engineering focus on leveraging advanced technologies and techniques to design and develop robust data solutions for clients. They play a crucial role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth. In data engineering at PwC, you will focus on designing and building data infrastructure and systems to enable efficient data processing and analysis. You will be responsible for developing and implementing data pipelines, data integration, and data transformation solutions. Job Title: Google Cloud Generative AI Lead Manager PwC US - Acceleration Center seeks a visionary Generative AI Solution Lead Manager to drive strategic problem-solving, architect innovative Generative AI and Agentic solutions, and provide technical leadership on Google Cloud Platform. Combining deep technical expertise in GenAI, Agentic AI, and GCP with strong leadership, you will shape high-value, strategically aligned Generative AI solutions for clients while ensuring responsible and compliant implementation. Responsibilities Strategic Solutioning & Architecture: Lead the translation of complex client business challenges into innovative Generative AI and Agentic solutions. Define technical strategy, solution designs, and comprehensive roadmaps, ensuring alignment with business objectives and delivering significant client value. Generative AI & Agentic AI: Provide architectural guidance and technical leadership for the design, development, and deployment of robust GenAI applications and intelligent agents on GCP. Drive the strategic selection and implementation of Agentic frameworks (e.g., Agent Development Kit, Gemini Enterprise / Agentspace, LangGraph, Langchain). GCP Ecosystem Mastery: Architect and optimize the strategic utilization of Google Cloud services including Vertex AI (Studio, Model Garden, Pipelines, Endpoints), Vector Search, Gemini Models, Document AI, Contact Center AI (CCAI). Leverage GCP for scalability, security, and reliability through GKE, Cloud Run, Cloud Functions, BigQuery, and Composer. Advanced Application Engineering: Oversee and provide technical leadership for building scalable Python-based back-end APIs (FastAPI, Flask) and integrating with front-end applications (React.js). Define API architectural patterns for robust and secure GenAI-driven applications. Data & MLOps Strategy: Define and implement data ingestion, preparation, and management strategies for GenAI models. Establish and enforce best practices for CI/CD pipelines and MLOps within GCP (e.g., Vertex AI Pipelines) for automated and observable deployments. Client & Stakeholder Engagement: Act as a key technical liaison, clearly articulating complex technical concepts to both technical teams and senior business leadership. Drive alignment, mentor junior team members, and foster a collaborative environment. Innovation & Thought Leadership: Serve as a subject matter expert in Generative AI and Agentic development, continuously evaluating emerging technologies and contributing to PwC's intellectual property and industry thought leadership. AI Governance & Responsible AI: Lead the implementation of AI governance frameworks, including the design and integration of LLM guardrails, ensuring solutions adhere to ethical AI principles, data privacy, compliance, and PWC's robust quality and security standards. Requirements Experience Profile: 9+ years of progressive experience in software development, data, or machine learning engineering. 5+ years hands-on experience with Google Cloud Platform (GCP). 4+ years experience in Data Engineering, Data Architecture, or Data Science. 2+ years leading Generative AI or Agentic AI development projects from conception to production. Technical Expertise: Expert Python proficiency (6+ years preferred), architecting and deploying scalable, production-grade applications. Deep expertise in FastAPI, Flask, and using Google Cloud APIs via Python SDK. Familiarity with React.js for front-end integration. Expert proficiency in SQL for advanced database design and optimization. Comprehensive understanding of data warehousing, data lakes, and data mesh concepts. Generative AI & Agentic Proficiency: Deep architectural understanding and prac