Principal AI Platform Engineer - Adaptiq
Confirmed on the employer's own hiring board on Nov 14, 2026. First seen by Alion on Oct 28, 2026.
Responsibilities
Develop Python services and tools supporting AI workloads.
Deploy, operate, and scale LLM inference services to meet the needs of active users and production traffic.
Configure and optimize model execution across multiple GPUs and compute nodes.
Build and improve automated deployment and configuration workflows.
Integrate and configure model-serving technologies.
Analyze system performance and improve scalability, resource efficiency, and reliability.
Design tests to evaluate production readiness and identify performance bottlenecks.
Improve monitoring, diagnostics, and recovery processes.
Experience
Strong Python development skills and experience building maintainable production software.
Hands-on experience operating LLM inference services in production, supporting active users and real-world traffic.
Practical experience deploying and serving models across multi-GPU configurations and multi-node environments.
Experience configuring and tuning an LLM-serving framework, such as vLLM or a comparable technology.
Practical understanding of GPU memory constraints and how they affect model deployment and execution.
Experience evaluating performance under load and interpreting latency, throughput, and resource usage.
Familiarity with techniques for reducing model memory requirements and improving inference efficiency.
Experience with infrastructure automation and infrastructure-as-code tools.