About this role
The AI Data modelling - Senior Associate supports client engagements in PwC Acceleration Centre India's Business & Supply Chain Operations practice. The role turns business requirements and complex data into AI-ready models and technical solutions, contributing to data-driven deliverables for Field Service & Operations Modernisation initiatives.
Responsibilities
- Design data models for AI/ML consumption, including embeddings, vector representations and retrieval-augmented generation (RAG) pipelines. Define schemas for structured and unstructured data used by LLM-based systems.
- Build and maintain pipelines for source-data ingestion, transformation and normalization. Work with stakeholders to map business entities into AI-ready structures, and optimize vector databases, knowledge graphs and relational stores for retrieval performance and accuracy.
- Manage assigned workstreams, interpret stakeholder feedback, mentor junior team members, maintain professional and technical standards, and build client relationships while navigating changing priorities.
Required qualifications
A bachelor's degree in computer science, Data Science or a related field; 4+ years of overall experience, including 2–3 years of relevant development experience; experience on real-time, client-facing AI projects; and hands-on expertise in AI/ML development and applied AI solutions.
What sets candidates apart: Experience developing model test suites and evaluation frameworks for accuracy, relevance and consistency; implementing guardrails against hallucinations, prompt injection, data leakage and unsafe outputs; and automating evaluations with golden datasets, regression tests and scoring rubrics. The posting also highlights red-teaming, adversarial testing, tracking precision, recall, latency and safety compliance, and using evaluation results to improve systems with engineering and product teams. Listed skills include Python, vector databases, RAG architecture, embedding models, LLM evaluation frameworks, guardrails and safety testing, prompt engineering, red-teaming, metrics and performance tracking, and Azure AI.