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Staff Software Engineer, Agentic Tools

Cribl

Remote · USJob$210–245K/yrSeen 2w agoSeen in employer's feed 5 days ago

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At a glance

Compensation
$210–245K/yr
Location
Remote · US
Work Authorization
Not specified

Olive lists jobs from US employers, including remote roles you can work from the United States.

Job overview

The Staff Software Engineer will build Cribl Engineering’s AI platform and productivity systems, including production agentic workflows, orchestration harnesses, and runtime infrastructure. The role focuses on reliable, observable, and secure tools that support software delivery across Engineering. The engineer will partner with teams to drive adoption, use the platform to solve real problems, and take designed projects from implementation through production operations.

Skills & qualifications

RequiredNice to have

Skills

Distributed SystemsTypeScriptModern JavaScriptNode.jsSoftware EngineeringContinuous DeploymentProgressive DeliveryMonitoringLLM WorkflowsAgentic CodingBackend ServicesIntegrationsAutomationAgent OrchestrationTool CallingEvaluation TechniquesGuardrail TechniquesAgent FrameworksExternal Tool IntegrationEvent-Driven SystemsQueuesStreamsPub/SubWebhooksObservabilityMetricsLogsTracesCommunicationDocumentationTeachingSecurityPermissions ManagementData AccessProblem-SolvingIndependent WorkKubernetesTerraformInfrastructure as CodeTemporal

Qualifications

Staff-Level Software EngineeringProduction Service ExperienceAgent Orchestration ExperienceEvent-Driven Systems ExperienceKubernetes Production ExperienceTerraform ExperienceTemporal Experience

Benefits

Medical Insurance
Dental Insurance
Vision Insurance
Paid Time Off
401(k) Match

Full job description

B2B SAAS data observability software. Join the company that's building the telemetry infrastructure for the AI era. At Cribl, we partner with IT and Security teams at many of the world's biggest enterprises, including half of the Fortune 100, to bridge the gap between AI ambition and infrastructure reality. As the AI Platform for Telemetry, we give customers the choice, control, and flexibility to manage and analyze telemetry for both humans and agents, so they can build what's next. We're one of the fastestgrowing private companies and a leading player in a massive, fastmoving market. With a global workforce, we're remotefirst and grounded in a simple idea: software is a people business. Cribl is the place where curious, collaborative people can do their best work, grow fast, and bring their full selves to the herd. Why You'll Love This Role You will help build Cribl Engineering's AI platform and productivity rails: the shared systems, runtimes, and workflows that let engineers use autonomous AI across the software delivery lifecycle. Instead of one-off prompts or single-feature AI experiments, you will focus on intent engineering, orchestration and harnesses, and production agent infrastructure that other teams can trust and extend. You will work with a small, high-impact team alongside tech leads, principals, and partner engineering groups. You will ship systems that plan, implement, review, test, and operate work with strong guardrails, then drive adoption until those tools become part of how Cribl builds software. You will also bring a builder mentality: use the product yourself to solve real team and Engineering problems, then turn that lived experience into better systems. Cribl strives to be a great place to work for everyone. As An Active Member Of Our Team, You Will... Design, build, and operate production agentic workflows and the platform harnesses they run on (orchestration, tool integrations, shared context, extension points for other teams) Practice intent engineering: turn goals into clear specifications, rules, constraints, and acceptance criteria that AI systems can execute reliably Stay current on AI tooling and practices, and evangelize what works across Engineering so partners adopt proven patterns Engage hard in design discussions and healthy debate while the direction is open, then pivot with equal energy into implementation once the team decides Build observability and guardrails: tracing, regression detection, human-in-the-loop controls, safe rollout, and operability for agentic systems others depend on Own critical pieces of agent runtime: job isolation, scheduling, execution environments, secrets and access, and production operations in the cloud Design and operate event-driven architectures where it fits (queues, streams, webhooks, async job fan-out) so agentic systems stay scalable and loosely coupled Ship safely and often: keep agentic systems on automated CI/CD paths with progressive delivery and clear rollback Bring a builder mentality: dogfood what we ship. Use the platform to unblock yourself and the team, surface sharp edges, and turn real usage into product and platform improvements Compress software delivery loops by improving how AI helps engineers write, test, review, debug, and validate changes in real repositories and pipelines Partner across Engineering to understand workflows, ship tools that fit how people work, and drive adoption through playbooks, examples, demos, and enablement Evaluate build vs. buy; stay current on models, agent frameworks, MCP-style tool protocols, and the broader AI tooling ecosystem Define and track success metrics for adoption, quality, reliabili ty, and satisfaction; use feedback and data to decide where to invest Partner on security and data access so tools are useful while respecting permissions and company policy Take designed projects from zero to production: own the path from agreed design through implementation, ollout, and day-two operability This position may include stand-by, on-call, or off-hours duties for systems you own If You've Got It - We Want It Staff-level (or equivalent) professional software engineering experience building and operating production distributed systems Strong TypeScript (and modern JavaScript) plus Node.js experience shipping production services; polyglot comfort is welcome, TypeScript is the primary stack for this team Strong software engineering fundamentals and the ability to ship quickly: design, testing, debugging, APIs/services, and code quality You have lived (or thrived in) a continuous deployment culture: automated pipelines, progressive delivery or safe rollout, monitoring and rollback, and a bias toward frequent, reversible production changes rather than infrequent manual releases Hands-on fluency with modern LLM and agentic coding workflows in production or serious internal platforms (not curiosity-only) Experience building backend services, integrations, automation, and internal tools; comfort across product surfaces when needed Professional experience with agent orchestration, tool-calling systems, evaluation or guardrail techniques, and connecting agents to reliable backend systems Familiarity with agent frameworks, orchestration layers, and integrating external tools and data sources into LLM-based systems (MCP or equivalent experience is a plus) Experience with event-driven systems: queues, streams, pub/sub, webhooks, or similar async patterns in production Observability fluency: metrics, logs, traces, and using them to operate and improve production systems Clear communication, documentation, and teaching ability; comfort driving adoption, not only writing code Good judgment around security, permissions, data access, and safe tool rollout Ability to problem-solve from first principles, make sound trade-offs, and drive work independently through ambiguity Nice to have Hands-on Kubernetes in production Terraform or similar infrastructure-as-code for cloud provisioning Temporal or other workflow-platform experience Deeper AWS / cloud-native ops fluency (IAM, networking, running production workloads end to end) #LI-JB1 #LI-Remote The salary for this role is dependent on geographic location and will be based on the individual candidate's job-related knowledge, skills, and experience. In addition to base salary, for sales and some sales-adjacent roles, employees are eligible to earn incentive compensation (commission). For all other roles, employees are eligible to participate in the Cribl Corporate Bonus Program. 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), and equity. Base Salary Range $210,000 - $245,000 USD 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 What Wage are you offering? 210000.00 to 245000.00 per Yearly

How this job compares

Set against the 8,420 open Software Engineering jobs on Olive Jobs, counted November 8, 2026.

Pay
  • This posting$210–245K/yr
  • Utah median$136–235K/yr70 salary ranges
  • US median$148–250K/yr6,332 salary ranges

This range's midpoint, $228K, is 16% above the Utah median midpoint ($196K) — in the top quarter of Software Engineering salary ranges in Utah.

Openings
Olive Jobs lists 116 open Software Engineering jobs in Utah and 8,420 across the US. 10% of them nationwide are listed as remote or flexible.
Hiring the most in Utah
Experience
Software Engineering postings that state a minimum ask for 7 years of experience at the median; the middle half ask for 5 to 10 years (6,438 postings).
Education
2,186 of the 8,420 open Software Engineering jobs (26%) ask for a bachelor's degree or higher.

Counted across the open, public US postings on Olive Jobs on November 8, 2026. Pay medians are the middle values of the low ends and of the high ends of postings that list both ends of a range in the same cadence (a yearly salary or an hourly rate); a range's midpoint is halfway between its ends. Pay and experience figures resting on fewer than 20 postings are left out.

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