AWS AI Engineer

Responsibilities

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• Implement agentic AI workflows for clinical source verification, discrepancy detection, and intelligent query generation.
• Build and integrate LLM-powered agents using AWS Bedrock + open-source frameworks (LangChain, AutoGen).
• Develop event-driven pipelines with AWS Lambda, Step Functions, and EventBridge.
• Optimize prompt engineering, retrieval-augmented generation (RAG), and multi-agent communication.
• Integrate AI agents with external systems through secure APIs.
• Experience in healthcare/Life Sciences AI solutions with regulatory compliance preferred
• Collaborate with data engineers for PHI/PII-safe ingestion pipelines.
• Monitor, test, and fine-tune AI workflows for accuracy, latency, and compliance.

Qualifications

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• Bachelor’s in Computer Science, Engineering, or related field.
• 3–6 years in AI/ML engineering with hands-on LLM/agentic AI development.
• Strong coding skills in Python/TypeScript and experience with LangChain, LlamaIndex, or AutoGen.
• Familiarity with AWS AI services (Bedrock, SageMaker, Textract, Comprehend Medical).
• Experience in API integrations and event-driven architectures.
• Experience in healthcare/Life Sciences AI solutions with regulatory compliance preferred
• Problem-solving mindset with ability to experiment and iterate quickly.