Collaborate and design solutions for challenging yet unique problems across hardware and software platforms, including servers, RAID, and various operating systems (Windows and Linux).
Candidates should possess familiarity with Back-End Web Development concepts, particularly for interfacing PLC systems with databases, APIs, dashboards, or industrial IoT platforms.
Own the infrastructure as code layer, defining all platform resources (Databricks workspaces, storage, networking, IAM) in Terraform with modular configurations. Establish staging and production environment separation with appropriate retention policies and CI/CD pipelines.
Define, monitor, and report on SRE metrics such as Service Level Indicators, Service Level Objectives, availability, latency, error rates, throughput, and error budgets
Kubernetes Service Platform Development of managed Kubernetes services with GPU-native orchestration, intelligent scheduling, distributed workload management, cluster lifecycle management, observability, resource isolation, and support for large-scale AI training and inference workloads
Kubernetes Service Platform Development of managed Kubernetes services with GPU-native orchestration, intelligent scheduling, distributed workload management, cluster lifecycle management, observability, resource isolation, and support for large-scale AI training and inference workloads
You will work on complex systems involving servo motion, gantry systems, multi-axis synchronization, robotics integration, and industrial PC-based control systems.
Build evaluation harnesses that measure output quality, faithfulness, hallucination rate, latency, and cost across model versions and prompt changes — governing whether AI features ship or roll back.
Work within established AI-native engineering workflows, collaborating with AI agents across implementation, testing, debugging, and documentation while validating every output.
Demonstrated experience across the Agent Development Lifecycle: specification, harness build, tool and MCP integration, evaluation, deployment, observability, and refinement.