LLM - Engineer - Senior Manager

Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Senior Manager Job Description & Summary At PwC, our people in data and analytics focus on leveraging data to drive insights and make informed business decisions. They utilise advanced analytics techniques to help clients optimise their operations and achieve their strategic goals. In data analysis at PwC, you will focus on utilising advanced analytical techniques to extract insights from large datasets and drive data-driven decision-making. You will leverage skills in data manipulation, visualisation, and statistical modelling to support clients in solving complex business problems. Growing as a strategic advisor, you leverage your influence, expertise, and network to deliver quality results. You motivate and coach others, coming together to solve complex problems. As you increase in autonomy, you apply sound judgment, recognising when to take action and when to escalate. You are expected to solve through complexity, ask thoughtful questions, and clearly communicate how things fit together. Your ability to develop and sustain high performing, diverse, and inclusive teams, and your commitment to excellence, contributes to the success of our Firm. Examples of the skills, knowledge, and experiences you need to lead and deliver value at this level include but are not limited to: Craft and convey clear, impactful and engaging messages that tell a holistic story. Apply systems thinking to identify underlying problems and/or opportunities. Validate outcomes with clients, share alternative perspectives, and act on client feedback. Direct the team through complexity, demonstrating composure through ambiguous, challenging and uncertain situations. Deepen and evolve your expertise with a focus on staying relevant. Initiate open and honest coaching conversations at all levels. Make difficult decisions and take action to resolve issues hindering team effectiveness. Model 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 When you join PwC Acceleration Centers (ACs), you step into a pivotal role focused on actively supporting various Acceleration Center services, from Advisory to Assurance, Tax and Business Services. In our innovative hubs, you’ll engage in challenging projects and provide distinctive services to support client engagements through enhanced quality and innovation. You’ll also participate in dynamic and digitally enabled training that is designed to grow your technical and professional skills. As part of the Data and Analytics team you will design and manage enterprise-grade Generative AI infrastructure. As a Senior Manager you will operationalize LLM-powered applications, making sure reliability and compliance while leading a team that drives innovation in AI solutions. Responsibilities Design and manage enterprise-grade Generative AI infrastructure Operationalize applications powered by large language models maintaining reliability Lead a team focused on innovation in AI solutions and compliance Collaborate with stakeholders to align AI initiatives with business goals Monitor and evaluate the performance of AI applications Foster a culture of creativity and technical excellence within the team Provide guidance on practices for AI implementation Communicate effectively with clients regarding AI project outcomes What You Must Have Bachelor's Degree 12 years of experience in DevOps, MLOps, Platform Engineering, Cloud Engineering, or Infrastructure Engineering roles Oral and written proficiency in English required What Sets You Apart Bachelor's or Master's Degree in Computer Science, Information Technology, Engineering, or a related field preferred HealthCare/PLS domain background preferred Consulting client and handling client stakeholder experience preferred Managing teams of 5-10 members preferred Excelling in programming with Python and/or Bash Building and managing CI/CD pipelines using GitHub Actions or Azure DevOps Pipelines Implementing secure networking patterns and zero-trust architecture Familiarity with vector databases and LLM deployment patterns preferred Staying updated with advancements in LLMOps and DevOps automation

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