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Generative AI Developer -Senior Associate

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Hybrid

Generative AI Developer -Senior Associate

PwC

Generative AI Developer -Senior Associate

Skills

Google Cloud PlatformPythonMachine LearningAIAWSAzure

2 months ago

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Important information


Contract type:

Permanent

Location:

Bengaluru, Karnataka, India

Work mode:

Hybrid

Published on:

4 September 2026

What they need


5+ years of total IT experience, including 2-3 years in AI/ML or Generative AI development. Must have hands-on experience building, testing, and deploying LLM-based or agentic AI applications in production or pilot settings.

Role & responsibilities

The Senior Associate Generative AI Developer will design, develop, and rigorously test end-to-end Generative AI and agentic AI applications. This role requires hands-on expertise with LLM APIs, RAG pipelines, prompt engineering, and multi-agent frameworks, combined with a disciplined approach to testing, performance monitoring, and optimization.

LLM & GenAI Development:

Design, develop, and maintain LLM-powered applications using APIs such as OpenAI, Azure OpenAI, Anthropic, or Cohere. Implement core GenAI workflows including summarization, classification, Q&A, and content generation.

Agentic AI Implementation:

Build and orchestrate multi-agent systems using frameworks like CrewAI, LangGraph, OpenAI Agents SDK, or Azure AI Agent Framework. Implement inter-agent communication, task routing, and tool orchestration for complex workflows.

RAG & Embedding Pipelines:

Implement retrieval-augmented generation pipelines involving embedding creation, chunking, and vector indexing using FAISS, Pinecone, Chroma, or Milvus. Ensure efficient retrieval for context-aware outputs.

Strong proficiency in Python, LangChain, LlamaIndex, CrewAI, and LangGraph

Deep understanding of LLM architectures, tokenization, embedding models, and vector databases

Experience with prompt testing and evaluation frameworks (TruLens, LangSmith, PromptLayer, DeepEval)

Familiarity with bias mitigation, safety testing, and Responsible AI principles

Knowledge of MLOps/LLMOps practices for deploying and monitoring AI models

Strong analytical mindset, documentation discipline, and collaborative approach

Exposure to at least one major cloud AI platform (Azure, AWS, GCP, or OCI)

Preferred Background:

Prior experience in building chatbots, intelligent assistants, summarizers, or document automation solutions using LLMs

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