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# Senior Software Engineer (AI Infra + Systems)

- **Company:** Jobot
- **Location:** United States (Remote available)
- **Experience:** Expert
- **Salary:** $170,000.0 - $200,000.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Software Applications, Cloud Computing, Distributed Systems, Python (Programming Language), Machine Learning, Systems Architecture, AI Infrastructure, Data Logging, Large Language Models, Concurrency, Generative AI, Backend, Containerization, AI Platforms, Kubernetes, Low Latency, Performance Monitor, Machine Learning Operations, Model Inference, Microservices
- **Published:** October 28, 2026
- **Apply:** https://www.dice.com/job-detail/d0e628b0-1ef3-472f-92a8-b74d3eeb3c93

## About the Role

* 5 + years of experience minimally. Fluent on the backend with Python and Scala
 * Experience designing, developing, and maintaining distributed systems and microservices in production.
 * Hands-on experience with Kubernetes, containerized applications, and cloud infrastructure.
 * Demonstrated ability to diagnose and resolve performance bottlenecks involving latency, concurrency, and system throughput.
 * Experience deploying or operating ML models through production APIs, with an understanding of inference performance.
 * Practical knowledge of MLOps principles related to model serving, monitoring, deployment, and operational reliability.
 * Familiarity with LLM-powered applications and the backend architecture supporting generative AI systems.
 * Strong understanding of production observability, including logging, metrics, tracing, and performance monitoring.

## Description

This position focuses on improving the performance, reliability, and efficiency of AI-powered applications while expanding the organization's model-serving capabilities. You'll work across backend engineering, distributed systems, and production AI infrastructure, with an emphasis on optimizing inference performance, reducing latency, and evaluating opportunities to move from managed AI services toward self-hosted models.

What You'll Do

 * Build & Maintain AI Backend Services: Develop and optimize production microservices using Python and Scala, supporting AI integrations, application APIs, and distributed backend systems.
 * Improve Scalability & Performance: Identify and eliminate bottlenecks involving latency, concurrency, throughput, and resource utilization across high-traffic applications.
 * Optimize Model Inference: Evaluate and implement model-serving architectures, including self-hosted inference, GPU utilization, autoscaling, and cost optimization.
 * Own Production Reliability: Manage the performance, monitoring, deployment, and operational health of AI services running in Kubernetes.
 * Drive Technical Improvements: Collaborate across engineering teams to improve system architecture, measure performance, and deliver scalable AI capabilities.