Software Engineer II, Delivery

Upstart is an AI lending marketplace that uses technology to expand access to affordable credit. The Software Engineer II, Delivery will build and operate release and deployment systems, developer tooling, and automation that enable safe, reliable software delivery to production. The role will also improve deployment visibility, reliability, observability, and AI-enabled delivery workflows.

Responsibilities:

• Build and improve services, automation, and developer tooling that enable engineering teams to safely release and deploy software to production
• Develop reliable deployment capabilities, including progressive rollouts, deployment health analysis, and automated rollback, to reduce the risk of production changes
• Improve visibility into releases, deployments, configuration, and production state so engineers can understand what changed, where it changed, and how it is performing
• Improve the reliability, performance, observability, and usability of Delivery systems by diagnosing recurring issues and implementing durable improvements
• Replace manual or fragmented release workflows with reusable, self-service capabilities that make the common path to production simple and consistent
• Use AI throughout software development and problem solving, and identify opportunities for AI-enabled automation that makes software delivery safer, faster, and easier to operate

Requirements:

• Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field (or its equivalent), plus 3 years of professional software engineering experience
• Experience developing production software using one or more general-purpose programming languages
• Experience designing, building, testing, and operating production software or infrastructure
• Experience working with cloud infrastructure, distributed systems, deployment systems, developer tooling, or backend services
• Experience independently delivering well-scoped software engineering projects from technical design through production operation
• Demonstrated experience using AI assisted development tools across multiple stages of the software engineering lifecycle, with an interest in continually evolving how you use these tools as their capabilities advance
• Experience with Kubernetes, AWS, containers, and infrastructure as code
• Knowledge of deployment platforms, release automation, internal developer platforms, or developer tooling
• Experience with progressive delivery practices such as canary deployments, automated health analysis, and rollback
• Experience with GitOps or deployment technologies such as Argo CD, Helm, or similar systems
• Experience using AI-assisted development tools across the software engineering lifecycle or building AI-enabled developer workflows and automation