We are seeking an AI Engineer experienced in building agentic AI workflows for healthcare and life sciences applications. The role involves developing and integrating LLM-powered agents using AWS Bedrock and open-source frameworks, creating event-driven pipelines, ensuring PHI/PII-safe data handling, and optimizing AI workflows for accuracy, latency, and compliance.
Responsibilities:
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:
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.
Agentic AI, LLM Development, AWS Bedrock, LangChain, AutoGen, LlamaIndex, Python, TypeScript, Event-Driven Architecture, AWS Lambda, Step Functions, EventBridge, API Integration, RAG (Retrieval-Augmented Generation), Prompt Engineering, Healthcare AI, Regulatory Compliance, SageMaker, Textract, Comprehend Medical, Data Ingestion, AI Workflow Optimization