AWS AI Engineer - US Healthcare & Generative AI

We are looking for an experienced AWS AI Engineer with strong expertise in artificial intelligence, generative AI, and US healthcare systems. The ideal candidate will have hands-on experience developing and deploying AI-powered applications on AWS, along with an understanding of healthcare workflows, data privacy, and HIPAA requirements. The role involves building scalable AI solutions using LLMs, RAG, and healthcare data while ensuring secure and reliable deployment in production environments.

Responsibilities:

• Design, develop, and deploy AI/ML and generative AI applications on AWS.
• Build AI solutions using LLMs, RAG, embeddings, semantic search, and vector databases.
• Develop backend services and AI pipelines using Python, FastAPI, or Flask.
• Use Amazon Bedrock, Amazon SageMaker, AWS Lambda, Amazon S3, API Gateway, and other relevant AWS services.
• Deploy and maintain AI applications in production AWS environments.
• Work with US healthcare data, including clinical documentation, EHR/EMR, medical records, claims, and healthcare operational workflows.
• Integrate healthcare systems and APIs, preferably using HL7 and FHIR standards.
• Implement secure data processing practices for PHI and support HIPAA compliance requirements.
• Build CI/CD pipelines and implement application monitoring, logging, and performance optimization.
• Collaborate with healthcare domain experts, data engineers, and product teams to deliver production-ready AI solutions.

Requirements:

• Experience: 4-8 years.
• Core Skills: Python, AWS, GenAI, LLMs, RAG, Healthcare Data, AWS Deployment.

AI/Generative AI:

• Strong Python programming skills.
• Hands-on experience with LLMs, generative AI, and AI/ML application development.
• Experience building RAG pipelines, embeddings, and semantic search solutions.
• Familiarity with LangChain, LangGraph, or LlamaIndex.

AWS & Deployment:

• Hands-on experience deploying AI/ML or GenAI applications on AWS.
• Experience with Amazon Bedrock and/or Amazon SageMaker.
• Knowledge of AWS Lambda, S3, IAM, API Gateway, and CloudWatch.
• Experience with Docker, CI/CD, and production deployment workflows.
• Understanding of cloud security, monitoring, and troubleshooting.

US Healthcare Domain:

• Prior experience working on US healthcare projects.
• Understanding of healthcare workflows involving claims, EHR/EMR, clinical records, or Revenue Cycle Management (RCM).
• Knowledge of HIPAA and secure handling of Protected Health Information (PHI).
• Familiarity with HL7, FHIR, ICD-10, or CPT is an advantage.

Good to Have:

• Experience with healthcare chatbots, clinical document summarization, or AI-powered claims processing.
• Experience with vector databases such as Amazon OpenSearch, Pinecone, Qdrant, or pgvector.
• Knowledge of LLM evaluation, guardrails, hallucination mitigation, and responsible AI.
• Experience with Terraform or AWS CDK.

Mandatory Requirements:

• Hands-on AWS deployment experience.
• Practical Python and AI/GenAI development experience.
• Previous US healthcare domain experience.
• Understanding of healthcare data security and HIPAA requirements.