Industry/Sector

Technology

Specialism

Software Engineering

Management Level

Senior Associate

Job Description & Summary

At PwC, our people in business application consulting specialise in consulting services for a variety of business applications, helping clients optimise operational efficiency. These individuals analyse client needs, implement software solutions, and provide training and support for seamless integration and utilisation of business applications, enabling clients to achieve their strategic objectives.

As a Guidewire developer at PwC, you will specialise in developing and customising applications using the Guidewire platform. Guidewire is a software suite that provides insurance companies with tools for policy administration, claims management, and billing. You will be responsible for designing, coding, and testing software solutions that meet the specific needs of insurance organisations.

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.

Key ResponsibilitiesCollaborate across teams: Partner with cross-functional groups to understand business requirements and identify opportunities for GenAI technology.Develop algorithms: Design and build advanced deep learning algorithms for generative models.Integrate AI solutions: Incorporate generative AI into existing workflow systems for smooth adoption.Research advancements: Stay up-to-date with the latest generative AI technologies and methodologies.Optimize performance: Fine-tune and enhance generative models for peak performance and efficiency.Troubleshoot implementations: Diagnose and resolve issues related to generative AI models and deployments.Documentation: Create and maintain comprehensive documentation detailing generative AI models and their applications.Communicate findings: Translate complex technical concepts for non-technical stakeholders.Required QualificationsExperience: 3+ years in data science or applied ML with shipped solutions; strong Python proficiency.Practical LLM experience: Building RAG pipelines, prompt/chain design, and experience with supervised or adapter-based tuning (LoRA/QLoRA).NLP/ML Tooling: Proficiency with PyTorch or TensorFlow, scikit-learn, and the Hugging Face ecosystem.Web development: Familiarity with Python web frameworks (Flask, FastAPI) for AI model web applications.Cloud-native development: REST APIs, microservices, serverless functions.Retrieval & vector search: Experience with embeddings, vector databases, and ranking/re-ranking techniques.Evaluation & experimentation: Designing metrics, A/B testing with sound statistical methods.Data skills: Strong SQL abilities; working with data lakes/warehouses and orchestration tools.MLOps/LLMOps: Experiment tracking (MLflow/Weights & Biases), model packaging, CI/CD for ML, monitoring, and incident response.Cloud deployment: Experience with Azure and/or AWS; containerization with Docker and Kubernetes.Communication: Ability to translate business needs into technical plans and communicate results clearly to diverse audiences.Preferred SkillsFrameworks: LangChain, Semantic Kernel, LlamaIndex; Azure OpenAI/OpenAI/Anthropic; Guardrails/safety toolkits (e.g., Azure AI Content Safety, Presidio).Fine-tuning & data generation: Dataset curation, synthetic data creation, RLHF/RLAIF exposure.Agents & tool-use: Function calling, planning, orchestration of multi-step agents.Performance engineering: Model distillation, quantization, ONNX/Triton, Ray for scaling.Event-driven integration: Kafka/Event Hubs, streaming inference with backpressure and retries.Certifications: Azure AI Engineer/Data Scientist, Databricks, or AWS ML Specialty.Professional & Educational BackgroundBachelor Degree in Computer Science, Data Science, Statistics, Engineering or equivalent

Travel Requirements

Not Specified

Job Posting End Date