AI Engineer | Bangalore | Immediate Joiner

Deloitte Shared Services India; Bengaluru; Hybrid; INR 3,500,000 - 5,200,000; Full time

Job summary

Deloitte Shared Services India in Bengaluru is seeking an experienced GenAI specialist to design, develop, and deploy Generative AI solutions using large language models. You will build and optimize Retrieval-Augmented Generation (RAG) pipelines, manage embedding-based search with vector stores, and refine prompts to boost model accuracy.

Collaborating with cross-functional teams, you will ensure scalable, reliable GenAI applications and guide deployment of AI frameworks across production

Qualifications

• Any Graduate with AI/DS focus and 8-12+ years of experience.
• Hands-on with GenAI frameworks and cloud AI platforms.
• Experience with RAG architectures, embeddings, and vector stores.
• Strong prompt engineering and LLM integration skills.
• Familiarity with data privacy, security, and compliance in AI.
• Proficient in modern development environments and AI tooling.

Responsibilities

• Design, develop, and deploy GenAI solutions using LLMs.
• Build and optimize RAG pipelines for enterprise use cases.
• Develop embedding-based search and vector store systems.
• Create, test, and refine prompts to improve model performance.
• Integrate LLMs through APIs and AI frameworks for production-grade apps.
• Collaborate with cross-functional teams on AI-driven solutions.
• Ensure scalability, reliability, and performance of GenAI apps.

Skills

GenAI frameworks

LangChain

LlamaIndex

Semantic Kernel

Azure OpenAI

Azure AI Foundry

AWS Bedrock

Google Vertex AI

RAG architectures

Embeddings

Vector Stores

Semantic Search

Prompt Engineering

LLMs

LLM integration

VS Code

IntelliJ

GitHub Copilot

Data Privacy

Security

Access Control

Cost Optimization

Education

B.Tech / B.Sc or related AI/DS field

Tools

VS Code

IntelliJ

GitHub Copilot

Vector databases

Job description

Your work profile

• Design, develop, and deploy Generative AI solutions leveraging Large Language Models (LLMs).
• Build and optimize Retrieval-Augmented Generation (RAG) pipelines for enterprise use cases.
• Develop and manage embedding-based search and retrieval systems using vector databases.
• Create, test, and refine prompts to improve model performance, accuracy, and response quality.
• Integrate and orchestrate LLMs through APIs and AI frameworks for production-grade applications.
• Collaborate with cross-functional teams to identify AI-driven business solutions and use cases.
• Ensure scalability, reliability, and performance of GenAI applications.

Key skills required

• Any Graduate- B.Sc/ B.Tech or in Artificial Intelligence, Data Science, or a related field.
• 8-12 years of experience
• Experience with GenAI frameworks such as LangChain, LlamaIndex, Semantic Kernel, or similar.
• Familiarity with cloud AI platforms such as Azure OpenAI, Azure AI Foundry, AWS Bedrock, or Google Vertex AI.
• Hands-on experience with Retrieval-Augmented Generation (RAG) architectures and frameworks.
• Strong understanding of Embeddings, Vector Stores, and Semantic Search concepts.
• Proven expertise in Prompt Engineering for optimizing LLM outputs.
• Experience working with Large Language Models (LLMs) such as GPT, Claude, Gemini, Llama, Mistral, etc.
• Hands-on experience in LLM initialization, integration, configuration, and deployment.
• Proficiency in using development environments such as VS Code/IntelliJ with GitHub Copilot or equivalent AI-assisted coding tools installed and actively utilized.
• Knowledge of Data Privacy, Security, Access Control, and Compliance within AI solutions.
• Understanding of LLM Cost Optimization techniques, including token management, caching, and model selection strategies.