Senior AI/ML Engineer

Brief Description

OUR IDEAL CANDIDATE

We are looking for a Senior AI/ML Engineer who wants to leverage cutting-edge Artificial Intelligence, including Generative AI, LLMs, and modern Agentic frameworks—to fix a broken healthcare system. The ideal candidate possesses a strong foundation in production machine learning, deep experience with cloud-native GenAI architectures (specifically on AWS), and a proven track record of working with sensitive healthcare data. You thrive in a high-impact, collaborative environment where you will design and deploy scalable AI-driven solutions that automate complex billing workflows, detect fraud, extract insights from unstructured claims, and power our next generation of AI products.

Responsibilities

• Design, build, and orchestrate Machine Learning, GenAI, and Agentic AI applications leveraging foundational models (via AWS Bedrock, SageMaker) for automated billing, cost prediction, and document intelligence.
• Design and build production-grade scalable Machine Learning (ML) pipelines integrating Object Character Recognition (OCR), Natural Language Processing (NLP), Retrieval-Augmented Generation (RAG), and agentic decision-making workflows to process complex medical claims and unstructured data.
• Establish end-to-end MLOps standards, automated model testing, and robust CI/CD pipelines for automated build, test, and release cycles of both ML models and AI services.
• Define, provision, and maintain secure cloud environments for AI/ML services using Infrastructure as Code (IaC) tools such as AWS CDK or Terraform.
• Develop APIs and microservices to enable seamless integration of ML/AI models into existing business applications.
• Collaborate with cross-functional teams (product, technology, operations, etc.) to align AI solutions with business goals.
• Implement techniques to improve transparency in AI decision-making, ensuring traceability and model explainability.
• Ensure compliance with healthcare data regulations (e.g., HIPAA, HITRUST, SOC 2, etc.).
  
  

Qualifications

• Bachelor's or Master's (preferred) degree in Computer Science, Data Science, Engineering, or a related quantitative field.
• 5 years of hands-on experience building, deploying, and maintaining production ML, GenAI, and Agentic solutions enterprise-wide for business applications.
• Deep practical knowledge of combining OCR engines (e.g., AWS Textract) with NLP, LLMs, VLMs, and AI foundational models to parse, structure, and query complex healthcare documents.
• Proven expertise within the AWS ecosystem (AWS Bedrock, SageMaker, Lambda, ECS/EKS) and proficiency in Python, PyTorch/TensorFlow, and modern GenAI and Agentic frameworks (e.g., Strands Agents, AgentCore, Kiro, etc).
• Strong foundation in algorithm design, data structures, containerization (Docker, Kubernetes), and ability to deploy ML models as scalable APIs using Flask, FastAPI, or similar frameworks.
• Strong hands-on experience using Infrastructure as Code (IaC) tools like AWS CDK or Terraform to manage cloud infrastructure, paired with practical experience building and maintaining CI/CD pipelines (e.g., GitHub Actions, AWS CodePipeline, etc).
• Experience working with healthcare data structures (e.g., insurance claims, EHRs, medical billing coding like CPT/ICD, or EDI 837/835 feeds).
• Strong understanding of HIPAA compliance, data masking, secure prompt/data handling, and AI safety guardrails.
• You are intellectually curious, obsessed with measurable business impact, and naturally inclined to build better solutions.
• Strong problem-solving skills and the ability to work independently.
  
  

How to Apply

To be considered for this opportunity, you must apply through our official Career Site by clicking the Apply button and completing the full application.

Only applications submitted through our Career Site will be considered. Applications submitted through other channels or third-party platforms will not be reviewed.