PwC
Website:
pwc.com
Job details:
At PwC, our people in legal services offer comprehensive legal solutions and advice to internal stakeholders and clients, maintaining compliance with regulations and minimising legal risks. These individuals provide strategic guidance and support across various industries. In privacy law and data protection at PwC, you will specialise in providing advice and guidance to clients on privacy laws and data protection regulations. You will help businesses navigate the complex landscape of privacy and data protection requirements, confirming compliance with applicable laws and regulations. Working in this area, you will assist in developing privacy policies, conducting privacy impact assessments, and implementing data protection measures to safeguard personal information.
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.
Skills
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.
Job Title: AI Solution Developer – “AI-in-a-Box” Use Cases
Job Type: Full-Time
Role Level & Experience
- Senior Associate (SA): 5+ years of relevant experience in AI/ML, software engineering, or solution development
About The Role
We are looking for a skilled AI Solution Developer to design and deploy modular AI solutions as part of our “AI-in-a-Box” initiative. This role combines hands-on AI/ML development, solution architecture, and end-to-end lifecycle management.
You will work with advanced AI technologies such as LLMs, RAG pipelines, microservices, Vector Databases, and Knowledge Graphs to build deployable solutions (Activate, Deactivate, Remove) within client environments with ease.
Expected Areas of Responsibility
- Solution Development & Engineering
- Design, develop, and deploy modular AI solutions using LLMs, RAG pipelines, and microservices
- Build scalable, reusable “AI-in-a-Box” accelerators for enterprise use cases
- Develop APIs and AI agents for use cases such as summarization, Q&A, and chatbots
- Architecture & Design
- Define end-to-end solution architecture including ingestion, retrieval, orchestration, and deployment
- Select appropriate models, embeddings, reranking strategies, and orchestration frameworks
- Ensure modular, extensible, and production-ready design
- Stakeholder Collaboration
- Work closely with business teams to translate requirements into technical AI solutions
- Communicate complex technical concepts to both technical and non-technical stakeholders
- Delivery & Lifecycle Management
- Manage the full lifecycle from PoC to production deployment and optimization
- Ensure scalability, reliability, and maintainability of deployed solutions
- Platform Integration & Engineering
- Build data pipelines to ingest content from platforms like SharePoint and enterprise databases
- Integrate AI solutions with enterprise tools such as Outlook, Teams, and Salesforce
- Develop and deploy microservices using FastAPI/Flask
- Performance Optimization & Monitoring
- Evaluate and improve retrieval accuracy, latency, and overall system performance
- Implement telemetry, logging, and evaluation frameworks
- Continuously optimize RAG pipelines and model performance
- Governance & Responsible AI
- Ensure adherence to Responsible AI practices, including evaluation, testing, and compliance
- Maintain data security, privacy, and governance standards
Senior Associate (SA)
- Hands-on development and implementation of AI solutions
- Contribute to architecture design and technical problem-solving
- Execute development, testing, and deployment tasks
- Collaborate closely with team members and stakeholders
Key Responsibilities
- Design and build modular AI solutions using LangChain, Semantic Kernel, or custom pipelines
- Develop APIs and AI agents for enterprise use cases
- Translate business requirements into scalable AI solutions
- Build ingestion pipelines and integrate enterprise data sources
- Implement embedding, reranking, and retrieval strategies for RAG pipelines
- Enforce structured outputs using Pydantic, function calling, or similar techniques
- Containerize and deploy solutions using Docker and CI/CD pipelines
- Monitor performance metrics and continuously improve system quality
Required Skills
- Strong Python skills with experience in AI frameworks (LangChain, Transformers, OpenAI SDK, LLaMA APIs)
- Hands-on experience with RAG pipelines, embeddings, and prompt design
- Familiarity with Knowledge Graphs (Apache Jena, SPARQL)
- Experience with Vector Databases (Pinecone, Chroma, etc.)
- Knowledge of embedding models (OpenAI Ada, Cohere, BGE/E5) and reranking techniques
- Experience building microservices (FastAPI, Flask)
- Exposure to multi-agent frameworks (LangGraph, CrewAI, AutoGen)
- Understanding of Model Context Protocol (MCP)
- Cloud experience with Azure (AKS, App Service, ACI) and DevOps tools
- Integration experience with enterprise platforms (Outlook, Teams, Salesforce)
Preferred Experience
- Delivery of at least 2 AI projects (PoC or production)
- Strong collaboration with business and technical stakeholders
- Knowledge of Responsible AI practices
- Experience in AI lifecycle management and packaging
Candidate Assessment Process (Optional)
Hands-On Exercises
- Build a RAG pipeline using vector databases and OpenAI/LLaMA
- Integrate with enterprise applications (e.g., SharePoint to Outlook workflow)
Technical Interview
- Solution architecture walkthrough (RAG, MCP, agents)
- Deployment strategy and DevOps lifecycle
- Performance testing, telemetry, and troubleshooting
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