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GenAI Engineer

IBM

Pune / Chennai

6+ years

Today

$38.6K–49.4K/yr

Full time

Onsite

Skills Required

LLM

RAG

Agentic AI

Gen AI

Multimodal AI

Semantic Retrieval

AI Integration

Prompt Workflows

Chatbots

Copilots

Enterprise Search

Content Generation

APIs

Databases

Document Repositories

Description

IBM is hiring a GenAI Engineer / Technical Consultant – AI Integration. The role designs and deploys enterprise AI and Generative AI solutions for business use cases.

Company: IBM

Role: GenAI Engineer

Location: Pune and Chennai

Experience

- 6 years of experience

Responsibilities

- Design, develop, test, and deploy enterprise Generative AI and AI integration solutions
- Integrate AI capabilities into enterprise applications, business workflows, APIs, and data platforms
- Build AI applications using LLMs, RAG, agentic AI, multimodal AI, prompt workflows, and semantic retrieval techniques
- Build and configure GenAI-based solutions such as chatbots, copilots, enterprise search assistants, and content generation tools
- Integrate AI services into enterprise applications, APIs, databases, document repositories, and business platforms
- Develop connectors and integration components between AI services, enterprise APIs, databases, and business applications
- Implement inference pipelines for real-time AI responses, prediction services, and workflow automation
- Design agentic workflows with tool orchestration, memory management, and context-aware reasoning
- Implement observability, monitoring, logging, performance tuning, and cost optimization for AI solutions




- Collaborate with cross-functional teams across the full solution lifecycle

Additional Responsibilities

- Deliver secure, scalable, and production-ready solutions
- Meet enterprise standards for performance, scalability, reliability, and cost
- Leverage AI-assisted development tools to improve productivity, accelerate delivery, and drive measurable business value
- Work within an AI-first engineering culture

More Skills Artificial Intelligence, Large Language Models (LLMs), Retrieval Augmented Generation (RAG), enterprise search assistants, content generation tools, enterprise applications, business platforms, connectors, integration components, inference pipelines, workflow automation, tool orchestration, memory management, context-aware reasoning, observability, monitoring, logging, performance tuning, cost optimization, AI-assisted development tools, modern engineering practices

Prepare for this role

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