Gen AI Engineer

Role / Project Description

We are looking for a GenAI Engineer to design, build, and deploy AI-powered solutions with a strong focus on document-centric workflows. The ideal candidate will have hands-on experience developing applications using Large Language Models (LLMs), Generative AI, Agentic AI frameworks, RAG, and Python-based backend development.

You will work closely with business and technology teams to build intelligent solutions that automate document processing, information extraction, summarization, knowledge retrieval, and workflow orchestration.

The role offers an opportunity to work on modern GenAI technologies and build scalable AI solutions for enterprise use cases.

Key Responsibilities

• Design, develop, and deploy Generative AI applications using modern LLMs and AI frameworks.
• Build and implement Agentic AI workflows capable of multi-step reasoning, decision-making, and task execution.
• Develop document intelligence solutions for processing, extracting, summarizing, classifying, and analyzing structured and unstructured documents.
• Design and implement Retrieval-Augmented Generation (RAG) solutions leveraging enterprise knowledge sources.
• Work with vector databases, embeddings, retrieval pipelines, and knowledge management solutions.
• Integrate AI solutions with internal applications, APIs, cloud platforms, and enterprise business systems.
• Develop and optimize prompts, agent workflows, retrieval strategies, and model performance to improve accuracy, reliability, and efficiency.
• Collaborate with cross-functional business and technology teams to understand requirements and translate them into scalable AI solutions.
• Troubleshoot, evaluate, and continuously improve GenAI applications and AI workflows.
• Ensure AI solutions meet required security, governance, scalability, reliability, and performance standards.

Required Skills

• 35 years of software engineering experience with strong proficiency in Python.
• Hands-on experience building applications using Generative AI and Large Language Models (LLMs).
• Strong understanding of RAG architectures, vector databases, embeddings, and semantic search.
• Practical experience with Agentic AI, AI agents, and multi-agent orchestration concepts.
• Strong understanding of document processing, document intelligence, information extraction, and knowledge management.
• Hands-on experience with one or more AI/GenAI frameworks such as LangChain, LangGraph, LlamaIndex, CrewAI, or similar frameworks.
• Experience integrating AI solutions with REST APIs, cloud platforms, and enterprise applications.
• Strong problem-solving, analytical, collaboration, and communication skills.
• Fluent English proficiency is required.
• Immediate joiners or candidates currently serving their notice period are preferred.

Nice-to-Have Skills

• Experience with AWS Agent Core.
• Hands-on knowledge of Model Context Protocol (MCP).
• Understanding of Agent-to-Agent (A2A) communication/protocols.
• Experience with AWS services for building and deploying GenAI/AI applications.
• Exposure to enterprise-grade AI governance, evaluation, observability, and security practices.