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Distyl AI

Builds AI systems for enterprise operations

Infrastructure Engineer - Agentic DevSecOps

DevOps EngineeringConfirmed live in the last 24 hours
Full-time

About the Job

Requirements

  • 10+ years of experience in software engineering, developer productivity, site reliability engineering, or related infrastructure engineering roles.
  • Experience enabling engineers to use coding agents through reusable tools, workflows, and guidance, with independent validation and scoped access.
  • Experience owning production build, test, and release infrastructure across services and teams, including versioned release bundles and compatibility testing.
  • Hands-on experience with build systems, dependency management, reproducibility, performance diagnosis, and caching.
  • Strong Python skills for building and debugging backend services and maintainable automation, and comfort navigating unfamiliar code, including JavaScript frontends.
  • Strong Linux fundamentals and experience building and maintaining secure container images; working knowledge of Kubernetes, GitOps, infrastructure as code, and cloud deployment.
  • Hands-on experience implementing software supply-chain controls, with demonstrated security judgment across permissions, credentials, dependencies, artifacts, and remediation.
  • Experience building developer platforms, automated remediation, or reusable agent tooling adopted by other engineers.
  • A record of improving build and test performance, release reliability, and tooling adoption using metrics and developer feedback.
  • Experience independently leading complex projects and migrations; the posting especially values a record of setting technical direction and driving adoption across teams, defending technical choices with evidence, and adapting to changing constraints.

Responsibilities

  • Set direction and priorities for build, test, release, and coding-agent infrastructure; choose tools and standards with engineering partners; and own implementation, adoption, and operation across teams.
  • Standardize repository conventions and reusable build and test workflows, and make builds reproducible and efficient through explicit dependencies, consistent tooling, and effective caching.
  • Build once and promote versioned bundles of immutable artifacts through release stages, with source traceability and test and security gates.
  • Partner with Platform, Runtime, and Customer Delivery on integration and compatibility testing, configuration and schema changes, and recovery; support customer-registry distribution and offline packaging where required.
  • Equip engineers with reusable coding-agent tools to diagnose failures, propose fixes, and handle routine work, including tests, scoped permissions, failure handling, and independent output validation; measure quality and time saved.
  • Implement artifact signing and provenance, software bills of materials, isolated build runners, scoped continuous integration credentials, and vulnerability gates; integrate dependency and container remediation into engineering workflows.
  • Understand engineers' workflows and remove friction with self-service tools, documentation, and diagnostics that distinguish code failures from tooling issues; use developer feedback to guide incremental migrations, earn adoption, and reduce manual work.
  • Track build and test latency, pipeline reliability, flaky-test rates, release lead time, and tooling adoption; use these signals and developer feedback to reduce flaky tests and bottlenecks; set service-level objectives and route actionable alerts to owners.

Desired Qualifications

  • Building and operating testing infrastructure in a microservices environment.
  • Distributing release artifacts to customer registries or restricted environments, including offline packaging.

About the Company

Distyl AI

Builds AI systems for enterprise operations

Distyl AI builds AI systems for large enterprises that need to automate complex business operations rather than isolated tasks. Its Distillery platform brings the tools for creating and running those systems together, while engineers and researchers work alongside customers to define the problem and put solutions into use. The company combines purpose-built software with implementation engagements across telecom, healthcare, insurance, manufacturing and retail, covering work such as customer service and supply chain decisions. Customers buy tailored enterprise deployments that connect business expertise with AI tools and are measured against operational outcomes. Founded in 2022, Distyl AI is headquartered in San Francisco, California.

Company size
51-200
Company stage
Late Stage VC
Total funding
$202M
Headquarters
San Francisco, CA
Founded
2022

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