Job Summary

We are seeking a skilled Generative AI Engineer with strong expertise in AWS cloud services, particularly AWS Bedrock and Amazon SageMaker. The ideal candidate will design, develop, and deploy enterprise-grade Generative AI solutions, leveraging Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and AWS-native AI/ML services to solve complex business challenges.

The role requires hands-on experience in building scalable AI applications, prompt engineering, model fine-tuning, and deploying production-ready GenAI solutions on AWS.

Key Responsibilities

• Design, develop, and deploy Generative AI applications using AWS Bedrock and Amazon SageMaker.
• Build and optimize Retrieval-Augmented Generation (RAG) architectures.
• Integrate foundation models and LLMs into enterprise applications.
• Develop AI-powered chatbots, virtual assistants, knowledge management systems, and intelligent automation solutions.
• Fine-tune, evaluate, and monitor machine learning and foundation models.
• Create prompt engineering frameworks and AI orchestration workflows.
• Implement vector databases, embeddings, semantic search, and document intelligence solutions.
• Develop secure, scalable, and high-performance cloud-native AI applications.
• Collaborate with business stakeholders, architects, data engineers, and software development teams.
• Ensure AI solutions comply with security, governance, and responsible AI standards.
• Stay updated with emerging GenAI technologies and AWS AI service offerings.

Required Skills Generative AI

• Strong experience with Large Language Models (LLMs).
• Prompt Engineering and Prompt Optimization.
• Retrieval-Augmented Generation (RAG).
• AI Agents and Agentic Workflows.
• Embeddings and Vector Search.
• Model Evaluation and Fine-Tuning.
• LLM Application Development.

AWS (Mandatory)

• AWS Bedrock (Must Have)
• Amazon SageMaker (Must Have)
• AWS Lambda
• Amazon S3
• API Gateway
• ECS/EKS
• CloudWatch
• IAM
• Step Functions

Programming

• Python (Mandatory)
• LangChain / LangGraph
• FastAPI or Flask
• REST APIs

Data & AI Ecosystem

• Vector Databases (OpenSearch, Pinecone, Weaviate, ChromaDB, FAISS)
• Knowledge Bases for Bedrock
• Model Monitoring and MLOps
• Data Processing Pipelines

Qualifications

• Bachelor's or Master's degree in Computer Science, AI, Data Science, Engineering, or related field.
• 4–10 years of software engineering, machine learning, or AI development experience.
• Hands-on experience building and deploying GenAI solutions in production environments.
• Experience with AWS cloud architecture and AI/ML services.

Preferred Skills

• Experience with Amazon Titan, Claude, Llama, Mistral, or other foundation models available through AWS Bedrock.
• Knowledge of Responsible AI, AI Governance, and Security.
• Experience with CI/CD pipelines and MLOps practices.
• Exposure to multi-agent systems and autonomous AI workflows.

Skills: aws,bedrock,foundation,prompt,amazon,cloud