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.
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