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. Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven decision making. You will work on developing predictive models, conducting statistical analysis, and creating data visualisations to solve complex business problems. Enhancing your leadership style, you motivate, develop and inspire others to deliver quality. You are responsible for coaching, leveraging team member's unique strengths, and managing performance to deliver on client expectations. With your growing knowledge of how business works, you play an important role in identifying opportunities that contribute to the success of our Firm. You are expected to lead with integrity and authenticity, articulating our purpose and values in a meaningful way. You embrace technology and innovation to enhance your delivery and encourage others to do the same. Examples of the skills, knowledge, and experiences you need to lead and deliver value at this level include but are not limited to: Analyse and identify the linkages and interactions between the component parts of an entire system. Take ownership of projects, ensuring their successful planning, budgeting, execution, and completion. Partner with team leadership to ensure collective ownership of quality, timelines, and deliverables. Develop skills outside your comfort zone, and encourage others to do the same. Effectively mentor others. Use the review of work as an opportunity to deepen the expertise of team members. Address conflicts or issues, engaging in difficult conversations with clients, team members and other stakeholders, escalating where appropriate. Uphold and reinforce professional and technical standards (e.g. refer to specific PwC tax and audit guidance), the Firm's code of conduct, and independence requirements. The Opportunity As part of the People Tech & AI team you will lead teams delivering governed Generative AI solutions, designing testing strategies, evaluation frameworks, and governance controls to promote reliable, ethical, and scalable AI agents. As a Manager you will supervise teams, manage client accounts, and apply leading practices across AI platforms, data pipelines, and integrations, while upholding PwC's values and professional standards. This role offers the chance to drive innovation in AI technology while fostering a collaborative environment that empowers team members and enhances client relationships. Responsibilities - Foster a collaborative environment to enhance team performance - Uphold professional standards and PwC values in every deliverable - Drive innovation in AI technology to meet client needs - Supervise team members and support their professional development What You Must Have - Bachelor's Degree - At least 6 years of experience in AI/ML engineering, data engineering, or software engineering - In lieu of a Bachelor's Degree, demonstrating, in addition to the minimum years of experience required for the role, three years of specialized training and/or progressively responsible work experience in technology for each missing year of college What Sets You Apart - Master's Degree preferred - Proven experience leading AI solution teams - Demonstrating understanding of LLMs and agent architectures - Possessing experience with Microsoft Power Platform - Bringing prior consulting or professional services experience - Establishing testing and validation standards for AI agents - Managing and coaching teams for continuous development - Building trusted client relationships and translating requirements - Designing and overseeing automated testing frameworks for Microsoft Copilot Studio and Google AgentSpace, including unit, integration, end-to-end, and regression testing, as well as low-code workflows, connectors, plugins, and grounding data - Leading governance of end-to-end AI agent pipelines and data flows, verifying integration correctness and resiliency, data quality, lineage, transformation accuracy, and embedded automated quality gates across CI/CD pipelines The salary range for this position is: $73,500 - $212,280. For residents of Washington state the salary range for this position is: $73,500 - $244,000. Actual compensation within the range will be dependent upon the individual's skills, experience, qualifications and location, and applicable employment laws. All hired individuals are eligible for an annual discretionary bonus. PwC offers a wide range of benefits, including medical, dental, vision, 401k, holiday pay, vacation, personal and family sick leave, and more. To view our benefits at a glance, please visit the following link: https://pwc.to/benefits-at-a-glance As PwC is an equal opportunity employer, all qualified applicants will receive consideration for employment at PwC without regard to race; color; religion; national origin; sex (including pregnancy, sexual orientation, and gender identity); age; disability; genetic information (including family medical history); veteran, marital, or citizenship status; or, any other status protected by law. PwC does not intend to hire experienced or entry level job seekers who will need, now or in the future, PwC sponsorship through the H-1B lottery, except as set forth within the following policy: https://pwc.to/H-1B-Lottery-Policy. Learn more about how we work: https://pwc.to/how-we-work For only those qualified applicants that are impacted by the Los Angeles County Fair Chance Ordinance for Employers, the Los Angeles' Fair Chance Initiative for Hiring Ordinance, the San Francisco Fair Chance Ordinance, San Diego County Fair Chance Ordinance, and the California Fair Chance Act, where applicable, arrest or conviction records will be considered for Employment in accordance with these laws. At PwC, we recognize that conviction records may have a direct, adverse, and negative relationship to responsibilities such as accessing sensitive company or customer information, handling proprietary assets, or collaborating closely with team members. We evaluate these factors thoughtfully to establish a secure and trusted workplace for all. Applications will be accepted until the position is filled or the posting is removed, unless otherwise set forth on the following webpage. Please visit this link for information about anticipated application deadlines: https://pwc.to/us-application-deadlines #LI-Remote #LI-Hybrid #BI-Hybrid

• Join the Engineering team as a Forward Deployed AI Engineer • Act as a resident AI expert within Individual Departments/Business Units • Function as engineer, solutions architect, and internal consultant • Design and build AI-powered application features using LLM APIs • Create agent loops that can select tools, execute actions, and summarize results • Develop chat-based analytical experiences connecting user questions to backend tools • Improve prompt quality and manage context windows • Use advanced AI coding tools to accelerate development while maintaining code quality • Embed directly with internal departments to identify where AI can drive efficiency • Lead the end-to-end implementation of AI solutions within operational contexts • Provide hands-on troubleshooting and support for AI models running in production mode

• Lead the technical vision, design and operation of the company’s AI gateway and core AI enablement platform • Define and implement standards for approved AI providers, models, data sources, shared tools and usage patterns • Build and maintain controls for access, routing, policy enforcement, auditability and financial operations reporting across AI usage • Implement required identity, logging and related controls in alignment with broader IT and security standards • Partner through the AI Enablement Council to translate business needs into scalable platform capabilities and guardrails • Support onboarding, documentation and internal enablement for business teams using approved AI tooling • Evaluate gateway platforms and ecosystem capabilities to improve flexibility, governance and business value • Drive reliable platform operations, issue resolution and continuous improvement across the AI environment

• Lead in the execution of the strategic direction for ML, NLP, LLM, and algorithm development within a world-class AI ML team, working closely with well-renowned experts in AI/ML modeling, ML engineering, data science, and data engineering • Partner with AI leadership to identify opportunities to leverage AI technologies to improve efficiency, productivity, and innovation • Collaborate closely with business stakeholders, data scientists, machine learning engineers, and software engineers to ensure smooth integration of machine learning models into production systems • Partner on the execution of custom ML, Gen AI, NLP, LLM Models for batch and stream processing-based AI ML pipelines including data ingestion, preprocessing modules, search and retrieval, Retrieval Augmented Generation (RAG), NLP/LLM model development and ensure the end-to-end solution meets all technical and business requirements, and SLA specifications • Complete the development and deployment of AI models and algorithms to solve complex problems • Ensure the robustness, scalability, and performance of AI systems and solutions • Stay updated on advancements in AI research and technology to guide initiatives • Foster a culture of innovation, collaboration, and continuous learning within the team • Coach, support, and provide mentorship for team members • Ensure stakeholder needs are met through effective communication and collaboration • Promote understanding of AI capabilities and limitations across the organization • Champion ethical AI practices and ensure compliance with regulatory standards • Address issues related to data privacy, security, and biases in AI systems • Develop policies that promote transparency and accountability in AI applications.