Job Role: Senior AI/ML Engineer (GenAI & AWS Bedrock)

Location: Hyderabad, India

Experience: 5+ Years

Work mode: Hybrid

About the role :

We are seeking a highly skilled Senior AI/ML Engineer with hands-on experience in Generative AI, Large Language Models (LLMs), AWS Bedrock, and Machine Learning Engineering. The ideal candidate will be responsible for designing, developing, and deploying AI-driven solutions leveraging cutting-edge GenAI technologies and AWS cloud services. You will work closely with data scientists, product teams, and cloud engineers to build scalable AI applications and intelligent automation solutions.

Key Responsibilities :

- Design, develop, and deploy AI/ML solutions using modern machine learning and Generative AI technologies.
- Build and implement GenAI applications using Amazon Bedrock, foundation models (Claude, Llama, Titan, etc.), and prompt engineering techniques.
- Develop Retrieval-Augmented Generation (RAG) architectures for enterprise AI use cases.
- Fine-tune, evaluate, and optimize Large Language Models (LLMs).
- Create scalable AI services and APIs using Python and cloud-native architectures.
- Develop data pipelines for AI model training, inference, and monitoring.
- Integrate vector databases and embedding models for semantic search and knowledge retrieval.




- Collaborate with cross-functional teams to translate business requirements into AI solutions.
- Implement MLOps best practices, model versioning, monitoring, and deployment automation.
- Ensure security, governance, and responsible AI practices in production environments.
- Stay updated with advancements in AI, LLMs, GenAI frameworks, and AWS services.

Required Skills & Experience

- 4+ Years of experience in Machine Learning, Artificial Intelligence, or Data Science projects.
- Hands-on experience in Generative AI/LLM-based application development.
- Strong programming skills in Python.
- Hands-on experience with AWS Bedrock and AWS AI/ML services.
- Experience in Prompt Engineering, RAG, embeddings, and vector databases.
- Robust understanding of LLMs, Foundation Models, Transformers, and NLP concepts.
- Experience with LangChain, LangGraph, LlamaIndex, AWS Strands, or similar GenAI frameworks.
- Knowledge of PyTorch, TensorFlow, Scikit-learn.
- Experience with AWS Lambda, ECS/EKS, S3, API Gateway, SageMaker, CloudWatch.
- Familiarity with vector databases such as FAISS, ChromaDB, Weaviate, or OpenSearch.
- Experience building REST APIs using FastAPI or Flask.
- Strong understanding of model evaluation, performance optimization, and ML lifecycle management.
- Knowledge of CI/CD and MLOps tools.

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