AI Engineer - Manager

Industry/Sector

Specialism

Management Level

Job Description & Summary

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.

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.

Job Title:

AI Solution Developer – “AI-in-a-Box” Use Cases

Job Type:

Full-Time

Manager:

• 8–10 years of experience with demonstrated expertise in leading AI solution design, architecture, and delivery
• 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
• 1. 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
• 2. 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
• 3. 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
• 4. Delivery & Lifecycle Management
• Manage the full lifecycle from PoC to production deployment and optimization
• Ensure scalability, reliability, and maintainability of deployed solutions
• 5. 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
• 6. 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
• 7. Governance & Responsible AI
• Ensure adherence to Responsible AI practices, including evaluation, testing, and compliance
• Maintain data security, privacy, and governance standards
• Manager
• Lead solution architecture and design decisions
• Own end-to-end delivery and client engagements
• Mentor and guide junior team members
• Drive best practices, standards, and reusable frameworks
• Manage stakeholders and ensure delivery timelines

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

Travel Requirements

Job Posting End Date