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# Senior AI Platform Engineer

- **Company:** THREE STORMS, LLC
- **Location:** United States (Remote available)
- **Experience:** Expert
- **Salary:** $200,000.0
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Artificial Intelligence, Big Data, Distributed Systems, Python (Programming Language), Machine Learning, NoSQL, Performance Tuning, SQL Databases, Large Language Models, Apache Spark, Reliability of Systems, Backend, AI Platforms, Solid Principles, Kubernetes, Information Technology, Machine Learning Operations, Docker, Microservices
- **Published:** October 18, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=7693d53426fca519

## About the Role

* Bachelor's or Master's in Computer Science, Engineering, or related field with 5+ years of experience.
 * Strong expertise in large distributed ML systems, MLOps, and software design principles.
 * Proficiency in Python, with knowledge of Java or Go a plus.
 * Hands-on experience with Docker, Kubernetes, and microservices architecture.
 * Familiarity with SQL, NoSQL, and big data frameworks like Spark.
 * Experience with LLMs or GenAI is highly desirable.

## Description

Are you ready to lead the development of cutting-edge AI systems within a high-growth healthtech environment? We're seeking an innovative and versatile Senior AI Platform Engineer to architect and enhance scalable machine learning infrastructure. You'll play a pivotal role in building robust AI/ML systems, collaborating across teams, and ensuring operational excellence in a fast-paced, mission-critical setting.

This is an opportunity to influence the future of healthcare technology through advanced ML workflows, microservices, and distributed systems. Your expertise will directly impact system reliability, model performance, and team capabilities, as you lead end-to-end initiatives and share knowledge across disciplines., * Design, build, and optimize production-grade AI/ML systems focusing on backend infrastructure and microservices.

 * Lead cross-functional projects, aligning scope, timelines, and dependencies to deliver impactful solutions.
 * Collaborate with AI/ML engineers to streamline model training, deployment, and monitoring processes.
 * Establish and enforce SLAs for latency, throughput, and system resources.
 * Develop tools for model lifecycle management, monitoring, and performance tuning.
 * Mentor team members and promote best practices in ML infrastructure.