We are looking for a highly skilled GenAI Engineer with strong hands-on experience in building AI-powered applications using Python and modern LLM orchestration frameworks. The ideal candidate should have practical expertise in developing Agentic AI solutions, RAG pipelines, multi-agent workflows, and scalable backend services integrated with Large Language Models (LLMs).
The role requires deep technical knowledge of AI application architecture, prompt engineering, vector databases, and enterprise-grade AI solution development.
Key Responsibilities
- 4+ Years of Design and develop scalable GenAI applications using Python
- Build intelligent AI agents and multi-agent workflows using Agentic AI frameworks
- Develop and optimize RAG (Retrieval-Augmented Generation) pipelines
- Work with LLM orchestration frameworks such as LangChain and LlamaIndex
- Integrate LLMs with enterprise systems, APIs, databases, and external tools
- Implement prompt engineering, context management, memory handling, and agent workflows
- Develop REST APIs and backend services for AI applications
- Work with vector databases and embedding models
- Optimize AI application performance, scalability, observability, and cost
- Collaborate with cross-functional teams including product, data engineering, and DevOps
- Ensure security, governance, and responsible AI practices in application development
Mandatory Skills
- Strong programming expertise in Python
- Hands-on experience with Generative AI (GenAI) application development
- Strong experience with LangChain
- Hands-on experience with LlamaIndex
- Experience in building Agentic AI / AI Agents
- Strong understanding of LLMs, prompt engineering, and AI orchestration
- Experience in RAG architecture and vector databases
- Knowledge of REST APIs and microservices architecture
- Experience with cloud platforms such as AWS, Azure, or GCP
- Familiarity with Docker and containerized deployments
- Strong debugging and problem-solving skills
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Skills Required
Docker, Gcp, Rest Apis, Azure, Aws, Python