Key Responsibilities
Design, build, and deploy Machine Learning and Generative AI solutions.
Develop and optimize RAG (Retrieval-Augmented Generation) architectures for enterprise knowledge retrieval.
Fine-tune, evaluate, and optimize Large Language Models (LLMs).
Build AI chatbots, virtual assistants, document Q&A; systems, and intelligent search applications.
Integrate vector databases for semantic search and retrieval.
Develop REST APIs and microservices for AI applications.
Deploy and manage AI workloads on AWS using cloud-native services.
Build scalable ML pipelines using MLOps best practices.
Implement prompt engineering and prompt optimization techniques.
Monitor model performance, latency, and cost optimization.
Collaborate with data engineers, software developers, and business stakeholders.
Ensure AI security, governance, and responsible AI practices.





Preferred qualification
7+ years of qualified experience in Machine Learning, Artificial Intelligence, Data Science, or Software Engineering, with a robust focus on AI/ML solutions.
3+ years of hands-on experience developing and deploying Generative AI, Large Language Model (LLM), and Retrieval-Augmented Generation (RAG) applications in production environments.
Proven experience designing, developing, and deploying scalable AI/ML solutions on AWS using services such as Amazon Bedrock, SageMaker, Lambda, S3, API Gateway, ECS/EKS, and related cloud technologies.
Robust proficiency in Python and AI/ML frameworks such as PyTorch, TensorFlow, Hugging Face Transformers, LangChain, and LlamaIndex.

📌 Ai Ml Engineer Hyderabad (India)
🏢 CGI
📍 India