Description:

- Architect and design end-to-end GenAI/LLM solutions leveraging AWS services such as Amazon Bedrock, SageMaker, Lambda, ECS/EKS, and S3
- Lead deployment of LLMs into production environments, ensuring scalability, low latency, cost-efficiency, and reliability
- Design and build Agentic AI systems — multi-agent orchestration, tool-calling, autonomous task planning, and agent-to-agent communication
- Design and implement RAG (Retrieval-Augmented Generation) pipelines, vector databases, and prompt engineering strategies for enterprise use cases
- Fine-tune, evaluate, and optimize LLMs for performance, cost, and accuracy
- Develop robust, production-grade Python code for GenAI pipelines, APIs, and agent frameworks
- Define best practices for LLMOps/MLOps, including CI/CD pipelines, model monitoring, versioning,



and governance
- Ensure solutions are secure, scalable, and compliant with enterprise architecture and data privacy standards
- Collaborate with cross-functional teams (data engineers, ML engineers, product managers) to translate business requirements into technical architecture
- Evaluate emerging GenAI/Agentic AI tools, frameworks, and AWS services, and provide recommendations for adoption
- Mentor engineering teams on GenAI, Agentic AI, and AWS architecture best practices.
- Create technical documentation, architecture diagrams, and present solutions to technical and non-technical stakeholders

📌 Gen AI Engineer (Hyderabad)
🏢 Quess Corp
📍 Hyderabad