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. Focused on relationships, you are building meaningful client connections, and learning how to manage and inspire others. Navigating increasingly complex situations, you are growing your personal brand, deepening technical expertise and awareness of your strengths. You are expected to anticipate the needs of your teams and clients, and to deliver quality. Embracing increased ambiguity, you are comfortable when the path forward isn't clear, you ask questions, and you use these moments as opportunities to grow. Examples of the skills, knowledge, and experiences you need to lead and deliver value at this level include but are not limited to: Respond effectively to the diverse perspectives, needs, and feelings of others. Use a broad range of tools, methodologies and techniques to generate new ideas and solve problems. Use critical thinking to break down complex concepts. Understand the broader objectives of your project or role and how your work fits into the overall strategy. Develop a deeper understanding of the business context and how it is changing. Use reflection to develop self awareness, enhance strengths and address development areas. Interpret data to inform insights and recommendations. 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 Data and Analytics Engineering team you will develop and implement AI solutions that enhance product offerings. As a Senior Associate, you will analyze complex problems, mentor junior team members, and maintain elevated professional standards while building meaningful client relationships. Responsibilities - Build and nurture meaningful relationships with clients - Utilize advanced analytical techniques to drive innovation - Work with cross-functional teams to achieve project goals - Uphold the firm's ethical standards and recommended practices What You Must Have - Bachelor's Degree in Computer Science, Data Processing/Analytics/Science, Artificial Intelligence and Robotics - 3 years of professional experience developing AI/ML systems or integrating AI into products What Sets You Apart - Master's Degree preferred - Possessing advanced proficiency in prompt engineering - Demonstrating experience deploying LLMs into production - Designing and optimizing RAG pipelines - Leading technical discovery in fast-paced environments - Collaborating effectively with cross-functional leaders - Advocating for responsible AI principles - Contributing to AI research or open-source communities - Demonstrating knowledge of orchestration tools such as LangChain, LlamaIndex, and experience with agent-based systems The salary range for this position is: $55,000 - $151,470. For residents of Washington state the salary range for this position is: $55,000 - $187,000. 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

• Build and operate LLM-powered internal solutions, tools, and automations end-to-end • Ship customer-facing AI features • Drive technical decisions from design through production rollout • Own systems in production, including monitoring, reliability improvements, and incident response participation • Build and maintain LLM evaluation workflows, including quality/safety checks, baselines, and regression detection • Partner with R&D, product, and security teams • Evaluate emerging AI technologies and patterns, and advocate adoption when justified

Role Description We are looking for a Applied AI Engineer to build and operate LLM-powered internal solutions, tools, automations, and customer-facing AI features end-to-end. We are not building AI for the sake of AI, or to follow hype or impress investors. We care about AI that works in real life and solves actual problems. Technology choices and product decisions are not simply handed down from the top. You will have room to shape the solution, challenge assumptions, choose the right tools, and influence the result. - Build and operate LLM-powered internal solutions, tools, and automations end-to-end - Ship customer-facing AI features - Drive technical decisions from design through production rollout - Own systems in production, including monitoring, reliability improvements, and incident response participation - Build and maintain LLM evaluation workflows, including quality/safety checks, baselines, and regression detection - Partner with R&D, product, and security teams - Evaluate emerging AI technologies and patterns, and advocate adoption when justified Qualifications - Strong software engineering fundamentals with hands-on ownership of production systems; Python required - Solid LLM application development experience, including context design, structured outputs, and orchestration - Hands-on experience with LLM evaluations, including experiment design, regression detection, gating, and observability - Experience building and operating backend services/APIs in production - Experience designing multi-service architectures and reliable integrations, including stable service contracts, retries, and failure recovery - Working knowledge of operating production databases, including schema design, indexing, migrations, and backup/restore - Hands-on experience with containerized workloads - Ability to balance output quality, latency, and cost in production AI systems Requirements - Experience with agentic systems or RAG, including evaluation - Experience building lightweight user interfaces - Experience shipping high-adoption internal developer or operations tooling - JavaScript/TypeScript - AWS deployment and operations experience - Experience with runtime isolation and sandboxing for sensitive execution - Experience in B2B SaaS, security, compliance, or data governance contexts Technology we use You do not need to have experience with every tool listed below, but this is the environment we work with now: - Python, uv, FastAPI, PydanticAI - PostgreSQL, Docker, Docker Compose - AWS: EC2, ECR, S3, Lambda - Interfaces and tooling: Streamlit or similar tools, pytest, ruff, pyright, OpenTelemetry Benefits - Fully remote work, giving you the flexibility you need in the modern world - A collaborative environment encouraging you to own your domain and implement best practices - Stable income, benefits, flexible working hours, and opportunities for promotion - Friendly and professional peers, eager to help and help you grow - A multitude of interesting challenges and opportunities

• Lead hands-on technical execution of AI engagements • Transform strategic vision into production-grade autonomous agent systems • Serve as a trusted technical advisor to executive stakeholders • Facilitate workshops to identify high-value use cases • Implement cutting-edge MLOps best practices for reliability and ethics • Deploy sophisticated models within major enterprise ecosystems • Test builder tools and stay ahead of AI advancements