Senior AI/ML Engineer

Latitude; Portland, Northern (OR, KY); Hybrid; USD 140,000 - 200,000; Full time

Job summary

Latitude is seeking a Senior AI/ML Engineer to build production-grade GenAI and agentic AI solutions in a healthcare context. You will leverage AWS Bedrock and SageMaker to design scalable ML pipelines for automated billing, claims processing, and document understanding.

Join a collaborative team focused on transparency, governance, and secure cloud infrastructure. Applicants should have significant hands-on GenAI, OCR/NLP, and MLOps experience within regulated environments.

Qualifications

• 5+ years of hands-on experience building, deploying, and maintaining production ML, GenAI, and Agentic solutions enterprise-wide.
• Strong background in production ML pipelines and cloud-native GenAI architectures.
• Experience with healthcare data, EHRs, and HIPAA/security controls.

Responsibilities

• Design and deploy ML/GenAI applications on AWS Bedrock, SageMaker, and related services.
• Build production-grade data pipelines with OCR, NLP, RAG, and agentic decisioning for medical billing workflows.
• Establish robust MLOps, CI/CD, testing, and monitoring for AI services.

Skills

GenAI

AWS Bedrock

SageMaker

Python

MLOps

OCR/NLP/RAG

HIPAA compliance

Education

Master's degree in CS/Data Science

Bachelor's degree

Tools

AWS CDK

Terraform

Docker

Kubernetes

Flask/FastAPI

Job 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.