Data Developer_ Senior Associate

PwC Acceleration Center India; Bengaluru; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

PwC Acceleration Center India is seeking an experienced AI Solution Developer to design and implement modular AI solutions. This role focuses on developing scalable AI solutions using advanced technologies such as LLMs and microservices, ensuring effective delivery from development to deployment.

The ideal candidate will possess strong Python skills, experience with AI frameworks, and a good understanding of RAG pipelines. This position offers an opportunity to work on diverse projects while collaborating with various teams to align technical solutions with business needs.

Qualifications

• Strong Python skills and hands-on experience with AI frameworks.
• Experience with RAG pipelines and embedding models.
• Knowledge of microservices and cloud platforms.

Responsibilities

• Design and develop modular AI solutions using LLMs and microservices.
• Translate technical requirements into AI solutions for stakeholders.
• Manage the lifecycle from proof of concept to deployment.

Skills

Python

AI frameworks (LangChain, Transformers, OpenAI SDK)

RAG pipelines

Knowledge Graphs

Vector Databases

Microservices (FastAPI, Flask)

Cloud experience with Azure

Job description

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

• 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)

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 summarisation, Q&A and chatbots.
2. Architecture & Design
   • Define end‑to‑end solution architecture including ingestion, retrieval, orchestration and deployment.
   • Select appropriate models, embeddings, re‑ranking 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 optimisation.
   • 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 optimise 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.

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, re‑ranking and retrieval strategies for RAG pipelines.
• Enforce structured outputs using Pydantic, function calling or similar techniques.
• Containerise 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 re‑ranking 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

• 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.