• Develop DevOps concepts, Containerization, and related product development for our program’s new modernized Platform systems using tools such as: Docker, Rancher, Kubernetes. • Work in an advanced product development team environment with systems and Software Platform Engineers. • Modern DevSecOps and Continuous Integration/Continuous Delivery techniques • Software lifecycle practices for large-scale defense project • Satellite ground system technologies

Cribl does differently. What does that mean? It means we are a serious company that doesn’t take itself too seriously; and we’re looking for people who love to get stuff done, and laugh a bit along the way. We’re growing rapidly - looking for collaborative, curious, and motivated team members who are passionate about putting customers first. As a remote-first company we believe in empowering our employees to do their best work, wherever they are. As the data engine for IT and Security many of the biggest names in the most demanding industries trust Cribl to solve their most pressing data needs. Ready to do the best work of your career? Join the herd and unlock your opportunity. Why You’ll Love This Role We are seeking a talented and experienced Staff AI Platform Engineer to help build Cribl’s new Corporate AI Systems team. In this pivotal role, you will design, deploy, and operate the governed AI platform that enables secure, scalable AI across Cribl’s internal systems and workflows. This is a foundational role on a newly established team created to provide the shared infrastructure, security guardrails, and reusable patterns needed to turn AI from fragmented experimentation into a durable company capability. You will be instrumental in standing up the shared AI infrastructure layer that powers high-impact use cases across GTM, Prod-Eng and G&A functions. The team’s mandate is to provide the “paved road” for AI at Cribl: secure access, governed integrations, reusable workflows, and a platform that enables teams to move faster without creating security, compliance, or operational risk. This role will report to the Sr. Director, Enterprise Applications and will partner closely with stakeholders across Enterprise Applications Engineering, Security, IT, and the business teams adopting AI to build the core platform that every subsequent AI initiative runs on. As An Active Member Of Our Team, You Will… As the Staff AI Platform Engineer, you will be the foundational builder of Cribl’s shared corporate AI platform. Your key responsibilities will include: - AI Platform Architecture & Operations: Define and own the architecture for Cribl’s internal AI platform, LLM deployments, MCP gateway design, orchestration patterns, and the shared services required to run AI use cases safely at scale. - Secure Access, Identity & Token Governance: Establish the identity and access model for AI systems, including distinct non-human identities, scoped credentials, audit logging, cost controls, and token governance infrastructure that supports least-privilege access. - Sandboxed Enablement & the Paved Road: Build safe, reusable sandbox environments and self-service patterns that allow business and technical teams to experiment with AI inside a governed framework rather than through ad hoc or unapproved tooling. - Enterprise Integration Architecture: Design the connective tissue between AI tooling and Cribl’s enterprise systems, helping define secure patterns for integrating with platforms such as Salesforce, NetSuite, Workday, Jira, Confluence, Slack, Google Drive, Glean, and other business-critical tools. - AI Security Partnership: Work hand in hand with the AI Security team to ensure secrets management, MCP governance, prompt-injection defenses, AI telemetry, and compliance-ready controls are built into the platform from day one rather than bolted on later. - Engineering Enablement: Stand up the platform capabilities needed for AI-accelerated development, including AI coding infrastructure and guardrails, DevOps pipeline integration, and secure workflows that help builders move faster without compromising quality or security. - Platform Reliability, Adoption & Operating Effectiveness: Define and track the metrics that matter most for a shared AI platform, including platform availability, reliability, usage, adoption, guardrail effectiveness, cost efficiency, and time to enable new use cases. Partner with adjacent stakeholders to support measurement of the business impact as the platform scales across the company. - We are a remote-first company and work happens across many time-zones – you may be required to occasionally perform duties outside your standard working hours If You’ve Got It - We Want It - Staff-level platform engineering experience: 7+ years of experience in software engineering, platform engineering, infrastructure engineering, internal developer platforms, or closely related technical roles, with a track record of building shared capabilities used by many teams. - AI platform fluency: Strong hands-on experience with modern LLM and agentic systems, including enterprise AI platforms, API-driven model integration, retrieval patterns, and the practical realities of getting AI safely into production. - Identity, security, and governance depth: Proven experience with OAuth, service identities, RBAC / ABAC / scoped permissions, auditability, secrets management, and secure-by-default architecture patterns. - Integration architecture expertise: Experience designing and operating integrations across enterprise systems, APIs, workflow platforms, and event-driven architectures in complex SaaS environments. - Practical systems mindset: Ability to balance speed, reliability, usability, and governance. You know how to build a platform that enables teams rather than slows them down. - Cross-functional communication: Strong written and verbal communication skills, with the ability to simplify complex technical tradeoffs for business leaders, security partners, and technical peers alike. - Builder mentality: You are comfortable creating the first version of the operating model, the runbooks, the patterns, and the platform itself. Ambiguity energizes you. - Outcome orientation: You care about measurable business impact, not just elegant architecture. You understand that the platform only matters if it helps Cribl ship useful, governed AI capability Preferred qualifications: - Experience with AWS Bedrock, Claude Code, or similar enterprise AI platforms. - Experience with MCP, skills, gateway technologies, API mediation, tool-use architectures for AI agents. - Familiarity with orchestration and workflow platforms such as n8n, Workato, and adjacent automation frameworks. - Experience deploying guardrails for AI-assisted engineering, including approval flows, policy enforcement, observability, and secure coding controls. - Familiarity with enterprise systems such as Salesforce, NetSuite, Workday, Jira, Confluence, Slack, Google Drive, and Glean. - Experience operating in a high-growth, remote-first B2B SaaS environment. - Comfort partnering closely with Security, IT, GTM Ops, Finance, People, and Support stakeholders. - Good jokes, or maybe better, bad jokes. - A love for goats. Salary Range ($169,000 - $235,000) The salary for this role is dependent on geographic location. The salary offered within the range described will be based on the individual candidate’s job-related knowledge, skills, and experience. In addition to a competitive salary, Cribl also offers a generous benefits package which includes health, dental, vision, short-term disability, and life insurance, paid holidays and paid time off, a fertility treatment benefit, 401(k), equity, and eligibility for a discretionary company-wide bonus. #LI-KJ1 #LI-Remote Bring Your Whole Self Diversity drives innovation, enables better decisions to support our customers, and inspires change for the better. We’re building a culture where differences are valued and welcomed, and we work together to bring out the best in each other. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, or any other applicable legally protected characteristics in the location in which the candidate is applying. Interested in joining the Cribl herd? Learn more about the smartest, funniest, most passionate goats you’ll ever meet at cribl.io/about-us.

Engineering @ MergeCo At MergeCo, we aren't just merging two companies; we are building a unified, scalable foundation for the future of our industry. Our IT philosophy is rooted in Governance over Administration. We don't just "fix tickets"—we build the secure, automated "rails" that allow our Engineering and Business teams to run their "trains" at high velocity. We are seeking a Senior Site Reliability & Platform Engineer who views infrastructure as code and security as a baseline requirement. You will be a key architect in defining our shared responsibility model, ensuring that while we provide the platform, the platform provides the guardrails. In this role, you will be a systems thinker who understands that IT is an enabler, focusing on building robust platforms rather than performing arbitrary third-party integrations. Day in the Life - Platform Engineering: Design and maintain our core Kubernetes and Cloud Native environments within GCP, AWS, and Azure, ensuring high availability, scalability, security, and seamless deployment patterns. - Observability & Reliability: Implement a comprehensive observability stack to provide deep insights into system health, performance, and security posture. - Cross-Cloud Strategy: While GCP is our primary home, you will provide expertise in integrating and bridging legacy or specialized workloads in Azure and AWS. - Automation & Lifecycle: Build automated, repeatable processes for provisioning and deprovisioning infrastructure, reducing manual toil to near zero. - The "Rails" Philosophy: Develop self-service tools that empower DevOps and Engineering teams to manage their own tool configurations while remaining compliant with MergeCo security standards. Who You Are - A Systems Thinker: You understand that IT is an enabler. You focus on building robust platforms rather than performing arbitrary third-party integrations. - Kubernetes Expert: You have deep experience managing production-grade clusters (GKE preferred) and understand the intricacies of service meshes, networking, and container security. - Cloud Polyglot: GCP is your native tongue, but you are fluent enough in Azure and AWS to navigate complex multi-cloud environments. - Security-First Mindset: You treat security as a core feature of reliability, not an afterthought. - Collaborative Partner: You prefer "Partnership" over "Gatekeeping," working with business units to define where the platform ends and their application Must Haves - 5+ years in SRE, DevOps, or Platform Engineering roles. - Expert-level Kubernetes orchestration and containerization (Docker/Containerd). - GCP Professional Cloud Architect or equivalent experience (IAM, VPCs, GKE, Cloud Operations). - IaC Mastery: Deep proficiency in Terraform, CDK, or Pulumi - Observability: Experience with Prometheus, Grafana, ELK, or Datadog to drive SLIs/SLOs. - Familiarity with Azure/AWS for hybrid-cloud connectivity and migrations. - Scripting/Coding: Proficiency in Go, Python, or similar for tooling and automation. Nice to Haves - Cloud Polyglot: Familiarity with Azure/AWS for hybrid-cloud connectivity and migrations. - Observability Tooling: Experience with Prometheus, Grafana, ELK, or Datadog to drive SLIs/SLOs. - Experience navigating complex multi-cloud environments. A Few of the Perks - Competitive benefits - Unlimited PTO - Remote work available for U.S.-based candidates - 401(k) with employer match - Paid parental leave - In-office benefits for those local to Dallas, TX: - - Catered lunches - Casual office atmosphere & located in the Design District - Fully stocked kitchen

• Define and own the architecture for Cribl’s internal AI platform, LLM deployments, MCP gateway design, orchestration patterns, and the shared services required to run AI use cases safely at scale • Establish the identity and access model for AI systems, including distinct non-human identities, scoped credentials, audit logging, cost controls, and token governance infrastructure that supports least-privilege access • Build safe, reusable sandbox environments and self-service patterns that allow business and technical teams to experiment with AI inside a governed framework rather than through ad hoc or unapproved tooling • Design the connective tissue between AI tooling and Cribl’s enterprise systems, helping define secure patterns for integrating with platforms such as Salesforce, NetSuite, Workday, Jira, Confluence, Slack, Google Drive, Glean, and other business-critical tools • Work hand in hand with the AI Security team to ensure secrets management, MCP governance, prompt-injection defenses, AI telemetry, and compliance-ready controls are built into the platform • Stand up the platform capabilities needed for AI-accelerated development, including AI coding infrastructure and guardrails, DevOps pipeline integration, and secure workflows that help builders move faster without compromising quality or security • Define and track the metrics that matter most for a shared AI platform, including platform availability, reliability, usage, adoption, guardrail effectiveness, cost efficiency, and time to enable new use cases • You may be required to occasionally perform duties outside your standard working hours