Urgent Hiring - AI Developer ( Senior Consultant)

PwC India; Mumbai; Presencial; INR 1 500 000 - 2 500 000; Tempo integral

Resumo da oferta

Price Waterhouse Cooper LLP is seeking an AI Engineer/GenAI Engineer with 3-5 years of experience to design, develop, deploy, and optimize AI-powered applications. You will work across the AI product lifecycle, integrating LLMs, RAG pipelines, vector databases, and enterprise data sources.

The role requires strong Python, API, and frontend fundamentals, plus experience with cloud platforms and CI/CD. You will collaborate with product, engineering, and business teams to deliver scalable AI

Qualificações

• Strong understanding of LLMs, prompt engineering, RAG architectures, embeddings, vector databases, semantic search, agentic AI, and tool calling.

Responsabilidades

• Design, develop, test, and deploy AI-powered applications, copilots, assistants, accelerators, and production-ready solutions.
• Build applications using LLMs, RAG pipelines, semantic search, tool calling, AI agents, and orchestration frameworks.
• Develop backend services, APIs, business logic, and user-facing interfaces for AI applications.
• Build ingestion and retrieval pipelines for enterprise knowledge sources including documents, databases, APIs, and business systems.
• Implement vector search, hybrid search, metadata filtering, and retrieval optimization techniques.
• Integrate foundation models and AI services from leading AI platforms such as Azure OpenAI, OpenAI, Anthropic, Vertex AI, and AWS Bedrock.
• Develop AI solutions that interact with enterprise tools and systems through APIs, webhooks, connectors, and modern integration protocols such as MCP.
• Optimize AI applications for accuracy, latency, reliability, scalability, and cost efficiency.
• Implement evaluation, prompt testing, tracing, and monitoring frameworks to improve AI output quality and system performance.
• Collaborate with product managers, architects, engineers, and business stakeholders to convert business requirements into working AI solutions.
• Contribute to reusable frameworks, shared libraries, engineering accelerators, and best practices for AI delivery.
• Ensure solutions follow security, compliance, data privacy, and responsible AI principles.

Conhecimentos

LLMs & prompt engineering

RAG architectures

embeddings

vector databases

semantic search

agentic AI

tool calling

LangChain/LangGraph/LlamaIndex

AI platforms (Azure OpenAI/OpenAI/Anth

Ferramentas

Python

FastAPI/Flask

React/Next.js/Streamlit/Gradio

Docker

CI/CD

Descrição da oferta de emprego

AI Engineer / GenAI Engineer (3-5 Years Experience)

Role Summary

We are building a high-impact AI engineering team focused on designing, developing, and deploying intelligent applications using modern Generative AI and machine learning technologies. This team works across the full AI product lifecyclefrom use-case discovery and rapid prototyping to production-grade deployment and continuous improvement. We are looking for an AI Engineer / GenAI Engineer with strong software engineering fundamentals and hands-on experience building AI-powered applications. The ideal candidate has practical experience with LLM-based systems, retrieval-augmented generation (RAG), agentic workflows, backend services, and cloud deployment. This role is ideal for someone who enjoys building real-world AI products, experimenting with new technologies, and delivering scalable business solutions.

Key Responsibilities

• Design, develop, test, and deploy AI-powered applications, copilots, assistants, accelerators, and production-ready solutions.
• Build applications using LLMs, RAG pipelines, semantic search, tool calling, AI agents, and orchestration frameworks.
• Develop backend services, APIs, business logic, and user-facing interfaces for AI applications.
• Build ingestion and retrieval pipelines for enterprise knowledge sources including documents, databases, APIs, and business systems.
• Implement vector search, hybrid sea

arch, reranking, metadata filtering, and retrieval optimization techniques.

• Integrate foundation models and AI services from leading AI platforms such as Azure OpenAI, OpenAI, Anthropic, Vertex AI, and AWS Bedrock.
• Develop AI solutions that interact with enterprise tools and systems through APIs, webhooks, connectors, and modern integration protocols such as MCP.
• Optimize AI applications for accuracy, latency, reliability, scalability, and cost efficiency.
• Implement evaluation, prompt testing, tracing, and monitoring frameworks to improve AI output quality and system performance.
• Collaborate with product managers, architects, engineers, and business stakeholders to convert business requirements into working AI solutions.
• Contribute to reusable frameworks, shared libraries, engineering accelerators, and best practices for AI delivery.
• Ensure solutions follow security, compliance, data privacy, and responsible AI principles.

Required Skills

Generative AI & Applied AI

• Strong understanding of LLMs, prompt engineering, RAG architectures, embeddings, vector databases, semantic search, agentic AI, and tool calling.
• Hands-on experience building AI applications using one or more frameworks such as LangChain, LangGraph, LlamaIndex, Semantic Kernel, CrewAI, AutoGen, or similar.
• Experience working with one or more AI platforms such as Azure OpenAI, OpenAI, Anthropic Claude, Google Vertex AI/Gemini, AWS Bedrock, or similar technologies.
• Understanding of grounding, hallucination reduction, prompt safety, and response quality improvement techniques.

Software Engineering

• Strong proficiency in Python.
• Experience building APIs and services using FastAPI, Flask, or similar frameworks.
• Experience building lightweight front-end or user-facing applications using React, Next.js, Streamlit, Gradio, or similar technologies.
• Good understanding of software design principles, debugging, testing, code quality, and version control.

Data, Retrieval & Integration

• Experience with vector databases such as Pinecone, Weaviate, FAISS, Chroma, Milvus, Azure AI Search, Elasticsearch/OpenSearch, or similar tools.
• Familiarity with document ingestion, chunking, embeddings pipelines, retrieval optimization, and enterprise search patterns.
• Experience integrating with APIs, third-party systems, databases, and enterprise applications.

Cloud & Platform Engineering

• Experience with Azure, AWS, or GCP.
• Familiarity with Docker, containerized deployments, and cloud-native application development.
• Understanding of CI/CD, deployment automation, and environment management.

Preferred Skills

• Experience with AI evaluation and observability tools such as LangSmith, RAGAS, DeepEval, Langfuse, Arize, Weights & Biases, or similar platforms.
• Familiarity with AI guardrails, responsible AI, access controls, and governance practices.
• Exposure to LLMOps practices such as prompt/version management, experiment tracking, tracing, and feedback loops.
• Experience building AI solutions for enterprise workflows, internal copilots, knowledge assistants, or customer-facing AI applications.