Senior Release Engineer, AI Platform & Infrastructure (Xora Portfolio Company)

This role owns the release and deployment path for Elemynt’s platform across secure enterprise and scientific computing environments.

You will build the systems that make every release versioned, reproducible, observable, and safe to operate. The work sits at the intersection of software engineering, infrastructure, site reliability, and customer delivery.

This is a deeply hands on senior role. You will take deployments from proof of concept through production, improve the playbook after each engagement, and help turn complex installations into repeatable engineering systems.

WHAT YOU WILL DO

• Own release engineering for the platform, including build promotion, quality gates, artifact management, and reproducible delivery practices.
• Build deployment tooling and automation that makes installs and upgrades reliable across varied enterprise environments.
• Design safe rollout, validation, health check, and recovery mechanisms for production deployments.
• Create operational visibility through logs, metrics, alerts, and support workflows appropriate for secure customer environments.
• Build controls for customer managed installations, including configuration validation, credential handling, certificate workflows, and documented recovery paths.
• Improve deployment reliability by debugging incidents, identifying root causes, and turning fixes into reusable automation.
• Partner with product, engineering, and customer facing teams to make deployment readiness part of how the platform is built.

• Bachelor’s or Master’s degree in Computer Science or a related engineering field, with 6 plus years building and shipping production software.
• Strong ownership of release processes, including CI and CD systems, automated tests, versioned artifacts, and production readiness gates.
• Deep hands on experience with container based deployments, infrastructure automation, and operating multi component systems.
• Experience deploying and supporting software in customer managed or restricted enterprise environments.
• Comfort working across more than one runtime environment, including cloud infrastructure, technical compute environments, and bare metal or cluster based systems.
• Strong operational debugging skills using logs, metrics, traces, and incident workflows.
• Experience with secrets, certificates, identity, permissions, and security controls for deployed software.
• Ability to own ambiguous, high stakes deployment work with limited scaffolding and strong execution discipline., * Exposure to scientific computing, simulation, engineering software, or other large scale technical workloads.
• Experience with GPU workloads or multi tenant compute environments.
• Experience with progressive delivery, Git based operations, or production rollout patterns.
• Familiarity with commercial scientific software deployment models and license management concepts.
• Experience packaging, versioning, monitoring, or operating machine learning models in production.
• Experience building the first version of an engineering function in an early stage company.