> Markdown version of [/jobs/ext/4009713-senior-ai-platform-engineer](https://www.wearedevelopers.com/jobs/ext/4009713-senior-ai-platform-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior AI Platform Engineer - **Company:** THREE STORMS, LLC - **Location:** United States (Remote available) - **Experience:** Expert - **Salary:** $180,000.0 - $200,000.0 - **Contract:** Permanent contract - **Skills:** Java (Programming Language), Artificial Intelligence, Big Data, Computer Programming, Data Structures, Python (Programming Language), Machine Learning, NoSQL, Software Engineering, SQL Databases, Large Language Models, Apache Spark, Generative AI, AI Platforms, Solid Principles, Kubernetes, Real-time Inference, Information Technology, Low Latency, Machine Learning Operations, Docker, Microservices - **Published:** October 29, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=06fcf3046473bf98 ## About the Role * Bachelor's or Master's degree in Computer Science, Engineering, or a related technical discipline. * 5+ years of industry experience in software engineering, ML infrastructure, MLOps, or related areas. * Experience designing or working with large-scale, distributed ML systems. * Strong understanding of MLOps, data structures, and software design principles. * Strong programming experience with Python. * Experience with additional backend languages such as Java or Go is valuable. * Hands-on experience deploying scalable ML models. * Strong knowledge of Docker, Kubernetes, and microservices architectures. * Exposure to LLMs and generative AI applications is a major plus. * Experience with SQL/NoSQL databases and Spark or similar big-data technologies is advantageous. ## Description This person will sit at the intersection of machine learning, backend engineering, and infrastructure, working closely with AI/ML, Data, and Infrastructure teams to productionize models and build reliable systems supporting training, inference, monitoring, and model management. The ideal candidate is comfortable working across complex distributed systems, can own projects end-to-end, and has strong experience building production-grade ML infrastructure., * Architect, design, and build scalable AI/ML systems for production environments, with an emphasis on backend distributed systems and microservices. * Lead cross-functional projects from initial scoping through execution, managing timelines, dependencies, and technical alignment. * Partner closely with AI/ML engineers to improve workflows around model training, real-time inference, monitoring, and troubleshooting. * Serve as a technical expert on ML infrastructure and provide guidance across engineering teams. * Own the reliability and operational performance of production ML systems. * Establish and maintain SLAs around latency, throughput, reliability, and resource utilization. * Build tooling for model management, continuous monitoring, deployment, and the broader ML lifecycle. * Mentor other engineers and contribute to engineering best practices.