Senior DevOps Engineer

About Invisible

Invisible is an Applied AI research company closing the gap between frontier models and the enterprise. We provide the platform infrastructure that makes AI work in production at scale: unify fragmented data, map complex processes, orchestrate and evaluate agents, and stand up hyper-personalized workflow applications fast for companies like Grubhub, Alliance Global, and Thomson Reuters. Where models fall short, we build RL environments and data to fix them. The result: a virtuous cycle between enterprise deployment and model training.

Recognized as Best Predictive Analytics Platform of the Year at the 2026 AI Breakthrough Awards, Invisible makes AI work.

About The Role

As a Senior DevOps Engineer, you'll own a domain of the Invisible platform — such as identity, compute, delivery, or agent infrastructure — and set the direction for how it works. You'll define the patterns that engineering teams across the company adopt, and be accountable for their reliability, security, and cost.

This is a role where judgement matters more than throughput. Deciding which problems are worth solving, recognising when the unremarkable solution is the correct one, and knowing when to decline a bespoke request from a client engagement are the day-to-day of the job.

We are looking for engineers with a first-principles understanding of platform practice, not just fluency in it. Code review, staged rollouts, change management, and least privilege were all designed around human engineers working at human speed. Those assumptions no longer hold cleanly. A meaningful part of this role is determining what still applies, what needs reworking, and what has to be built from scratch.

What You’ll Do

Own a platform domain end to end, including architecture, roadmap, reliability, security posture, and cost

Lead design and trade-off discussions across performance, scalability, cost, security, and reliability, and document the decisions

Build multi-tenant infrastructure that client engagements can self-serve onto without the Platform team becoming a delivery bottleneck

Advance our agent-native engineering model — safe execution environments, credential and secret handling, internal tooling and MCP servers, and evaluation of where agents genuinely improve outcomes

Set standards for how the engineering organisation works with coding agents, including review practice, context engineering, and what should and shouldn't be automated

Partner with client-facing engineering teams to understand their infrastructure requirements and translate them into reusable platform capability

Mentor engineers on the team, review their designs, and raise the technical bar without absorbing their work

Own on-call and post-incident review practice

What We Need

Kubernetes & Cloud: Proven experience designing and operating production Kubernetes at multi-team scale, on GCP, Azure, or AWS

Infrastructure as Code: Deep experience with Terraform, Helm, and GitOps delivery, including a clear view of how these degrade when implemented poorly

Platform Security: Strong grounding in identity and SSO, workload identity, secrets management, and network policy. You can reason about a threat model directly rather than through a compliance checklist

Programming: Strong Python. You build tooling, not only configuration

AI Coding Agents: Exceptional practical command of agentic coding tools, and a track record of making other engineers more effective with them. You've built the harnesses, guardrails, and internal tooling, and you have a considered view of where agents deliver value and where they quietly cost more than they save

Engineering Judgement: A first-principles grasp of why platform practices exist. You can identify which survive contact with agentic engineering, which need reworking, and which were only ever ceremony

Communication: Excellent written communication. You can take an ambiguous problem and produce a document that makes the decision clear to technical and non-technical stakeholders alike

A track record of shipping infrastructure that other engineers depend on, and the willingness to challenge an approach when the room has already agreed on it

We weight demonstrated capability over years of experience or formal qualifications

What’s In It For You

Invisible is committed to fair and competitive pay, ensuring that compensation reflects both market conditions and the value each team member brings. Our salary structure accounts for regional differences in cost of living while maintaining internal equity.

Bonus and equity is included in all full-time, non commission offers. Final compensation is determined by a combination of factors, including location, job-related experience, skills, knowledge, internal pay equity, and overall market conditions. Because of this, every offer is unique. Additional details on total compensation and benefits will be discussed during the hiring process.

You can find more information about our geographic pay tiers here . During the interview process, your Invisible Talent Acquisition Partner will confirm which tier applies to your location. For candidates outside the U.S., compensation is adjusted to reflect local market conditions and cost of living.

What It's Like to Work at Invisible:

At Invisible, we’re not just redefining work—we’re reinventing it. We operate at the intersection of advanced AI and human ingenuity, pushing the boundaries of what’s possible to unlock productivity and scale. Ownership is at the core of everything we do. Here, you won’t just execute tasks—you’ll build, innovate, and shape the future alongside world-class clients pushing the boundaries of AI.

We expect bold ideas, relentless drive, and the ability to turn ambiguity into opportunity. The pace is fast, the challenges are big, and the growth is unmatched. We’re not for everyone, and we’re okay with that. If you’re looking for predictable routines, this isn’t the place for you. But if you’re driven to create, thrive in dynamic environments, and want a front-row seat to the AI revolution, you’ll fit right in.

• Country Hiring Guidelines:
• Invisible is a hybrid organization with offices and team members located around the world. While some roles may offer remote flexibility, most positions involve in-office collaboration and are tied to specific locations. Any location-based requirements or hybrid expectations will be communicated by our Talent Acquisition team during the recruiting process.

• AI Interviewing Guidelines:
• Our hiring team thoughtfully uses AI to support an efficient, engaging, and inclusive interview process. Since AI can also be a helpful tool for candidates, we've outlined expectations for using it ethically throughout your interview journey. Click here to learn more about how we use AI and our guidelines for candidates.

• Accessibility Statement:
• We are committed to providing reasonable accommodations for individuals with disabilities. If you require an accommodation to participate in the application or interview process, please submit your request using our accommodation request form. A member of our team will follow up to support your request.

• Equal Opportunity Statement:
• We’re an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, or veteran status, or any other basis protected by law.