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
