At our company Software Technologies, we secure the world - and now we're securing the AI revolution. We're building a Workforce AI Security Platform: a cloud-native, multi-tenant SaaS platform that governs, protects, and enables safe AI adoption across global enterprises. This is a greenfield opportunity to help architect the infrastructure backbone of a platform that will define how organizations adopt AI at work securely.
We're looking for a Senior DevOps Engineer who owns infrastructure end-to-end, ships with confidence, and raises the reliability bar without being asked. You will work closely with backend, full-stack, and security teams, as well as DevOps teams across other our company organizations, to build a highly available, reliable, and secure production environment. If you get energized by building systems that scale, pipelines that teams love, and platforms that never sleep - this role is for you.
Key Responsibilities
Own and evolve our cloud infrastructure across multi-region production environments, end-to-end.
Lead our GitOps deployment model - designing and maintaining declarative, automated deployment workflows with zero manual gates.
Build, maintain, and optimize CI/CD pipelines with a strong focus on developer experience, reliability, and speed.
Initiate, implement, and champion an AI-first DevOps & SRE ecosystem - identifying opportunities, building AI agents and intelligent automation, and driving their adoption across engineering operations.
Develop automation frameworks for provisioning, scaling, observability, and incident response, leveraging AI-powered tooling and agentic workflows to reduce toil.
Operate and improve our observability platform: metrics, logs, alerting, dashboards, SLOs/SLIs, and on-call tooling.
Champion zero-trust secrets management and credential-less authentication patterns across the stack.
Partner with architects and engineering leadership on cloud cost optimization, availability, and performance.
Build internal tooling and automation that multiplies engineering velocity across the organization.

We're hiring a Senior/Principal Site Reliability Engineer to own production reliability for Cortex Agentix Endpoint Security (following an acquisition of KOI Start Up) as it scales. You'll define and operate our SLOs and error budgets, lead high-severity incident response, and ensure our Kubernetes and AWS infrastructure stays stable under growth. You'll also build and supervise the AI agents that handle routine alert triage and monitor tuning, focusing your own time on the reliability engineering that requires human judgment. This role is a strong fit for someone who treats reliability as an engineering discipline and enjoys ownership, incident command, and applying AI to operational work.
Your Impact:
Own reliability as an engineering discipline - define SLIs, set SLOs, and run error-budget-based decision-making so "how reliable are we" becomes a number that governs how fast we ship.
Own production incidents end-to-end - lead response, mitigation, and resolution for high-severity incidents, and drive blameless postmortems that feed real fixes back into the system.
Own the reliability and capacity of production infrastructure as we scale - forecasting headroom, validating scaling behavior under load, and keeping latency and error rates within SLO.
Run and evolve Kubernetes environments so releases and infra changes are safe by default across hundreds of tenant apps.
Own, build, and supervise our SRE AI agents that triage alerts, review monitors, resolves and summarize incidents. Set and expand the trust ladder that governs what the agents do autonomously, what needs approval, and what stays human. This is a core part of the role.
Improve observability and incident response - raise signal quality, cut alert noise, and own the monitoring the triage agents depend on.
Eliminate toil - relentlessly identify manual, repetitive operational work and remove it through automation and agents, protecting engineering time for reliability work that only humans can do.
Analyze operational data across incidents, alerts, deployments, infra health, and cost to find reliability gaps, capacity risks, and automation opportunities.
Evaluate and introduce new tools and AI-assisted approaches, balancing innovation with reliability, cost, and operational simplicity.

is looking for a DevOps engineer to own our infrastructure end to end.
You would be our only one. There is no platform team to join and no one to hand you a ticket queue. There is plenty of work, and most of it is on this page. You will set the technical direction as we grow, report to the Head of Engineering, and work directly with every engineer on the team.
We run on AWS and Kubernetes and deploy through GitOps. Our use of AI in engineering is growing quickly, and the infrastructure behind it has not caught up yet. Building that is a real part of this job.
What Youll Do:
Own all of our infrastructure. Kubernetes, AWS, and the core services around them. The foundation was built properly and the team has kept it running between other priorities. You are not inheriting a mess. What it has not had is a full-time owner. Reliability, cost, security posture, and the roadmap all become yours.
Own CI/CD. Every services build and deploy pipeline, and the self-hosted runner infrastructure underneath. We ship fast and we are working on shipping faster. One of our engineers is automating more of it right now, and you will take that over and push it further. The interesting problem is adding the safety a growing company needs without turning deploys into something people dread.
Help us shape the infrastructure behind our AI development. Our engineers use coding agents every day and that use keeps growing. We do not have a clear path for the infrastructure behind it yet, and you will help us find one. One direction we are exploring is moving agents off laptops and into the cloud, with a sandbox environment per engineer so an agent keeps working after the laptop is closed. Deciding whether that is the right answer, and building what we choose, is part of this job.
Scale how we deploy to customers. Some customers need us to run inside their own environment. We already do this, but each deployment takes too much hands-on work. You will make it repeatable, faster, and secure, and give our engineers the tooling to support customers directly.
Own our observability. Metrics, logs, alerting, and dashboards. Decide what is worth waking someone for, and keep the cost of watching under control.
Own infrastructure security and support our compliance work. Hardening, IAM, secrets, and vulnerability management. You will help us keep our SOC 2 compliance, which customers require before they will work with us, and help answer their security reviews. We sell to security teams, so they ask hard questions.
Keep our data recoverable. Backups, restore testing, and a disaster recovery plan for RDS Postgres and ClickHouse that we have actually rehearsed.
Partner with engineers on solutions, not tickets. You are the person developers come to when they need infrastructure to do something new.