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.

What am I going to do?
Full Ownership: Drive infrastructure initiatives through their entire lifecycle, taking accountability from initial design to delivery and long-term operations.
Kubernetes Orchestration: Architect, implement, and maintain production-grade Kubernetes clusters, ensuring they remain scalable and resilient under high-scale demand.
Cloud Architecture: Design and manage robust AWS environments, including VPC, IAM, and EKS, to support a highly available platform architecture.
Infrastructure as Code: Utilize Terraform to build and evolve our environment, applying configuration management principles to all IaC workflows.
CI/CD Excellence: Support and improve our deployment pipelines using Jenkins and GitHub Actions to maintain a fast development velocity.
Observability: Implement comprehensive monitoring solutions with Prometheus and Grafana to ensure deep visibility into platform health.
Operational Resilience: Join the DevOps on-call rotation, taking responsibility for mitigating production issues and maintaining site reliability.
Tooling & Innovation: Continuously evaluate and adopt tools - security and otherwise - that raise the bar on engineering efficiency and security posture at our company.

As a Platform DevOps Engineer for us, you will lead DevOps for our SaaS product. You will serve as the products primary DevOps owner, with end-to-end responsibility for infrastructure, Production availability, reliability, and development and deployment workflows. The role is designed to establish a scalable DevOps capability as the product and organization grow.

Key Responsibilities
Own the end-to-end cloud-native infrastructure for us, including Development, Test, and Production environments.
Design and build scalable, secure, and reliable infrastructure for an active SaaS product.
Lead CI/CD, deployment, and release-management processes using GitHub Actions, GitOps, and Argo CD.
Manage and scale Kubernetes, Docker, Helm, and public-cloud infrastructure using Terraform.
Establish and lead observability, monitoring, alerting, and incident-response capabilities.
Participate in on-call rotations, resolve Production incidents, lead postmortems, and drive preventive improvements.
Partner with R&D teams to improve product performance, scalability, reliability, and security.
Develop automation and scripting tools, and promote AI-powered code assistance and development practices to improve operational speed and quality.
Build operational processes, infrastructure standards, and documentation that support the future growth of the DevOps capability.

You'll own and evolve the infrastructure and reliability of our production platform - a distributed, data-heavy system running on AWS and Kubernetes. You'll work closely with engineering to keep our services fast, reliable, and observable as we scale, while continuously improving our automation, deployment, and operational processes.
This role is a fit for someone responsible and hands-on, who wants to contribute to the team effort, take ownership, and keep learning and expanding their capabilities.
What You'll Do
Design, build, and operate scalable, resilient infrastructure on AWS and Kubernetes.
Own reliability: define SLOs/SLIs, improve observability, and drive down toil through automation.
Manage and tune our core data and workflow systems - ClickHouse, PostgreSQL, Kafka, and Temporal - for performance and reliability at scale.
Build and maintain CI/CD and GitOps workflows using ArgoCD and GitHub.
Manage infrastructure as code with Terraform.
Lead incident response, run postmortems, and drive systemic improvements.
Establish and improve engineering and operational processes suited to a company operating at scale.
Partner with development teams to make the right reliability, cost, and scalability tradeoffs.

Required Senior SRE Engineer /Senior DevOps
Were on a mission to help companies unlock reality and reach their full potential. As a Senior Site Reliability Engineer (SRE), youll play a key role in shaping our new Production Reliability domain. Youll drive reliability initiatives, lead cross-team projects, and ensure our SaaS platform stays robust, scalable, and efficient. This is a high-impact, hands-on role that demands technical expertise and a proactive approach.
You'll Own
Design, build, and maintain scalable, fault-tolerant systems.
Define and enforce reliability processes, SLOs, SLIs, and SLAs.
Lead complex incident responses, including on-call rotations and postmortems.
You'll Solve
Challenges related to observability, testing, production stability, and development productivity.
Reliability improvements through data-driven decisions.
Complex production incidents.
You'll Impact
Build automation, tooling, and self-service capabilities.
Collaborate with engineering, product, and support teams to embed reliability into everything we do.
Mentor engineers and promote operational excellence across the organization.

We are looking for a proactive and skilled Software Infrastructure Developer with a strong Agentic AI focus to join our team. In this role, you will design and build the infrastructure, tooling, and AI-powered automation that keep our engineering systems reliable, scalable, and intelligent.

You will be responsible for embedding GenAI and agentic capabilities into our internal developer platforms and CI/CD workflows - creating frameworks, libraries, and multi-agent systems that accelerate automation, improve system stability, and unlock new levels of engineering productivity. This is a hands-on role for someone who thrives at the intersection of infrastructure engineering and applied AI.

The ideal candidate brings deep technical expertise in Python (FastAPI) and/or TypeScript, Kubernetes, CI/CD (Jenkins, GitHub Actions), containerization, and cloud infrastructure - combined with hands-on experience building LLM-powered applications, agents, MCP servers, and RAG pipelines.

What you'll be doing:
AI Platform Development: Design and build internal AI platforms, reusable SDKs, libraries, tools, and MCP servers for agentic applications.
Agentic Workflow Development: Develop single- and multi-agent workflows covering planning, tool selection, delegation, state and memory management, execution, retries, fallbacks, error recovery, and human-in-the-loop approval.
AI-Powered Infrastructure & CI/CD: Integrate AI capabilities into Kubernetes infrastructure and Jenkins/GitHub Actions pipelines to improve development, testing, deployment, and operational workflows.
AI Observability & Evaluation: Implement agent tracing, prompt and tool-call logging, latency and error monitoring, token and cost tracking, regression testing, and failure analysis.
AI Security & Governance: Apply guardrails, access controls, auditability, and governance practices to ensure agents operate safely and reliably.
End-to-End Platform Ownership: Own AI platform capabilities from architecture through production and build reusable solutions that accelerate adoption across engineering teams.
Cross-Functional Collaboration: Collaborate with engineering and business teams to identify high-impact AI opportunities and translate them into scalable technical solutions.
AI Research & Innovation: Evaluate emerging AI frameworks, models, and cloud technologies and promote their adoption where they provide measurable value.

We're looking for a Senior Platform Engineer to join our CTI Group. We're a startup that builds a lot, so you'll work across a wide range of systems and tools, build new platforms and services, and have real influence over where the platform goes next.
You'll work on the platform behind our CTI products: the microservices running on Kubernetes, the cloud and on-prem environments around them, and the infrastructure behind the systems. There's a lot still to build, and you'll have a real say in what comes next.
Responsibilities
Own what you build end to end, from design through implementation to running it in production.
Design and build the internal platforms, tools, and services other engineering teams rely on, and add new ones as we grow.
Make architectural decisions across infrastructure, applications, networking, security, and data.
Design, build, and maintain our cloud and on-prem environments.
Build and operate the infrastructure behind our AI/ML systems at scale.
Manage and evolve our Kubernetes environments.
Build and maintain CI/CD pipelines, deployment automation, and Infrastructure-as-Code with Terraform.
Build security into the platform, from IAM and secrets management to network policies.
Set up the monitoring and observability that show us how the platform is doing.
Design for scalability, availability, performance, and resilience in high-scale production systems.
Apply Infrastructure-as-Code practices (Terraform) end to end.

We are seeking a DevOps software engineer for our agentic AI team. If you are excited to work at the frontier of AI agents and want your work to multiply the output of hundreds of engineers, we want to hear from you.

What you'll be doing:

Build AI agents that solve real engineering problems across the networking stack, with a focus on the infrastructure and services that bring them into reliable daily use.

Design, build, and operate the platforms that make those agents reliable: MCP tools, service APIs, cloud and on-prem services, and the systems behind them.

Work broadly across networking architecture teams to identify high-impact AI use cases and turn them into working solutions.

Drive rapid and responsible AI adoption across the organization: establish best practices, guardrails, and evaluation methods so teams embrace agentic workflows with confidence.

Build evaluation and observability pipelines that measure AI-agent behavior and platform reliability on real production workloads.