Senior AI DevOps Developer, Tooling and Operations

ActiveState Software Inc.•,

9d•Remote

About The Position

ActiveState secures open source for the AI coding era. Through our Curated Catalog, we deliver vetted open-source components that are built from source, continuously remediated in SLSA Level 3 infrastructure, and delivered through the tools teams already use, giving security and engineering teams a trusted foundation whether code is written by humans or AI. At ActiveState, we run highly scalable, 100% automated systems that rebuild open-source languages and libraries from source, securely and repeatably, across many languages and platforms, and deliver them to customers through our Curated Catalog. Doing this at scale is a problem of security, orchestration, and automation, and this team owns the systems that make it possible. You'll implement, maintain, and improve the infrastructure beneath everything we build, keeping our product and engineering organization productive. That means automating cloud deployments, strengthening the security and monitoring of apps and services running in Kubernetes, Nomad, and other cluster systems, and continually improving how we build and ship open-source at scale. Increasingly, that work centers on agentic engineering: designing, building, and operating the agentic workflows and the AI agents that drive them, that automate real work across our systems. You'll stand up tool-using agents that can detect, diagnose, and remediate issues, run them reliably and safely in production (guardrails, permissions, evaluation, observability, and human-in-the-loop where it matters), and make agentic tooling accessible to the rest of engineering. This is both how we work and where ActiveState — and modern software engineering — is headed. We're a polyglot team that reaches for the best tool for the job, whether that's Golang, Javascript, Python, Docker, Kubernetes, GraphQL, or an AI agent, with practices built on GitHub, pull requests, code review, CI, measurement and testing, and agile development. Quality matters as much as speed, so you'll write solid tests and documentation and help us keep improving. Developers across ActiveState rely on you to handle the hard parts of networking, deployment, monitoring, and reliability, and to make AI and agentic tooling safe and productive to reach for. Customers rely on that same work for a product that's stable, reliable, secure, and available. This job is a mixture of tools development and operations. Sometimes it makes sense to write our own tools, and other times to adopt, configure, and deploy open source projects or cloud-native services. Your experience and expertise will be essential in deciding which approach best suits our needs, including how we bring agentic AI capabilities into production safely and responsibly. The team is remote first, primarily in the US and Canada, so we coordinate with each other and the rest of the company using Slack for chat, Zoom for video calls and screen sharing, Jira, and the Google Suite. We use open source software whenever possible, and we contribute back to the open source ecosystem. We embrace open sourcing both libraries and tools developed in-house as long as those are not mission-critical code. If reducing complexity, improving reliability, and helping your fellow developers ship faster is the kind of work that excites you, we'd love to meet you.

Requirements

An operations mindset: keeping systems running and running well, even if you didn't create them.
Experience maintaining complex software systems along with the ability to design non-trivial applications and components from scratch.
Practical experience creating tools for other developers, OR practical experience administering, securing, and automating cloud deployment environments.
A problem-solving mindset, where you enjoy debugging as well as anticipating and avoiding potential problems.
Strong experience with at least one programming language, and shallow experience with several. Polyglots are welcome!
Hands-on experience building agentic systems including LLM agents, tool use / function calling, and agent orchestration, and bringing them into production reliably, securely, and repeatably.
The judgment and autonomy to help shape how we adopt AI/ML and agentic approaches, and where they fit on our technical roadmap.
Excellent written and spoken skills, both technical and non-technical. You'll need to collaborate closely with your developer teammates, as well as be able to have coherent conversations with people from QA, sales, marketing, and other parts of the company.
A willingness to engage in the process of defining our work through conversations with product management, other engineering teams, and the rest of the company.
The ability to help others on the team become better at their jobs. This includes mentoring teammates in AI/ML and agentic engineering, through supporting, trusting, and generally being a team player.

Nice To Haves

DevOps tooling, automation, or application development.
Supporting AI/ML systems in production (MLOps), including data pipelines, RAG, vector databases, model serving, GPU infrastructure, or techniques like RLHF.
Security Operations Center experience.
SRE and Chaos Engineering.
Agile processes, including breaking large projects up into smaller stories, estimation, working in branches (GitHub Flow), code review, and CI.
IT automation frameworks and tools such as Terraform, Ansible, Chef, Puppet, or Salt.
Microservices, message queues, and workflow orchestration systems such as Argo.
Docker, Nomad, and Kubernetes, especially in cloud environments.
Golang, Perl, Python, Javascript, Ruby, or Tcl development experience, especially an understanding of their respective language communities and their toolchains.

Responsibilities

Implement, maintain, and improve the infrastructure beneath everything we build, keeping our product and engineering organization productive.
Automate cloud deployments.
Strengthen the security and monitoring of apps and services running in Kubernetes, Nomad, and other cluster systems.
Continually improve how we build and ship open-source at scale.
Design, build, and operate agentic workflows and AI agents that automate real work across our systems.
Stand up tool-using agents that can detect, diagnose, and remediate issues.
Run agents reliably and safely in production (guardrails, permissions, evaluation, observability, and human-in-the-loop where it matters).
Make agentic tooling accessible to the rest of engineering.
Handle the hard parts of networking, deployment, monitoring, and reliability for developers.
Make AI and agentic tooling safe and productive to use.
Decide whether to write custom tools or adopt, configure, and deploy open-source projects or cloud-native services.
Bring agentic AI capabilities into production safely and responsibly.
Coordinate with team members and the rest of the company using Slack, Zoom, Jira, and Google Suite.
Use open source software whenever possible and contribute back to the open source ecosystem.
Open source libraries and tools developed in-house, as long as they are not mission-critical code.
Reduce complexity, improve reliability, and help fellow developers ship faster.