{"schemaVersion":"jobsearcher.job.v1","id":"aa7a23776e43e7522ef5885a","url":"https://jobsearcher.com/jobs/aa7a23776e43e7522ef5885a","canonicalUrl":"https://jobsearcher.com/jobs/aa7a23776e43e7522ef5885a","title":"Sr. Software Engineer - Engineering Enablement","description":"Location\nUS Remote\nEmployment Type\nFull time\nLocation Type\nRemote\nDepartment\nResearch & Development\nCompensation\n$150K – $190K\nMeridianLink runs a comprehensive background check, credit check, and drug test as part of our offer process.\nIt is not typical for offers to be made at or near the top of the salary range. The actual salary will be determined based on experience and other job-related factors permitted by law including geographical location.\nMeridianlink offers:\nInsurance coverage (medical, dental, vision, life, and disability)\nFlexible paid time off\nPaid holidays\n401(k) plan with company match\nRemote work\nAll compensation and benefits are subject to the terms and conditions of the underlying plans or programs, as applicable and as may be amended, terminated, or superseded from time to time.\n#LI-REMOTE\n\nPosition Summary\nThis is a senior-level individual contributor on the Engineering Enablement team. The team builds the shared CI/CD infrastructure, AI development tooling, and sandbox environments that hundreds of R&D engineers depend on. A core part of that mission is advancing MeridianLink's AI-native development program — building the harnesses, agent infrastructure, and shared tooling that move engineering teams from ad-hoc AI usage toward autonomous, repeatable development pipelines. This role owns a significant chunk of that platform and drives adoption across engineering teams.\nThis is a hands-on role: real code, real infrastructure, direct engagement with engineering teams. The measure of success is how much faster you make everyone else.\nKey Competencies\nWhat it means to be a Senior Engineer at MeridianLink\nSenior individual contributors own their work end-to-end, identify problems before they're surfaced, and make the engineers around them better. Senior engineers at MeridianLink are active, daily users of AI-assisted development tools.\nTechnical Execution & Delivery\nOwns features and infrastructure end-to-end: design through production release, limited guidance required\nIdentifies edge cases and failure modes independently within assigned scope\nParticipates actively in code review with constructive, specific feedback\nSurfaces blockers early rather than waiting for check-ins\nCraft & Professionalism\nWrites tests that catch regressions without over-engineering the suite\nMonitors shipped work, responds to issues, and follows incidents to resolution\nPuts institutional knowledge into shared systems rather than individual heads\nCI/CD & Build Systems\nDesigns pipeline abstractions (templates, shared jobs, reusable configs) that work across multiple teams and tech stacks\nReasons clearly about the tradeoffs between standardization and flexibility at org scale\nKeeps pipelines healthy, observable, and continuously improving\nAI Tooling & Developer Infrastructure\nBuilds and maintains shared MCP servers, agent orchestration harnesses, and reusable skills and plugins\nUnderstands LLM developer tooling in practice: tool definitions, agent loops, prompt management\nDesigns shared tooling with product thinking: requirements gathering, feedback triage, prioritized backlog\nSandbox & Agent Infrastructure\nOwns the shared infrastructure layer for autonomous AI agent environments: orchestration, provisioning, observability, cost controls, and security guardrails\nPartners with product teams on their individual sandbox configs while maintaining the platform underneath\nEnablement & Engineering Advocacy\nTreats engineers as customers: office hours, documentation, feedback loops\nMeasures platform impact with DORA metrics, adoption rates, and time-to-productivity data\nCloses the gap between shipping tooling and driving adoption\nExpected Duties\nCI/CD Platform\nOwn and evolve shared infrastructure: templates, shared jobs, abstractions, and standards across R&D\nResolve systemic reliability issues: flaky tests, slow builds, caching inefficiencies\nPartner with teams during migrations and help them adopt shared abstractions without disrupting delivery\nAI Tooling Platform\nBuild and maintain shared MCP server infrastructure connecting AI harnesses to internal systems (Jira, Confluence, GitLab, internal APIs)\nDevelop agent orchestration infrastructure: scheduling, observability, cost controls, security boundaries\nBuild reusable harness skills, slash commands, and workflow scripts that ship as internal plugins\nSandbox Infrastructure\nOwn the shared infrastructure for AI agent sandbox environments: container orchestration, environment templates, networking, resource management\nBuild and maintain orchestration and admin tooling: provisioning, lifecycle management, health monitoring, cost tracking\nImplement security guardrails for data isolation between sandbox environments\nEnablement & Adoption\nDrive AI tooling adoption through documentation, onboarding programs, office hours, and direct team engagement\nMaintain the internal best practices hub and AI development playbook\nInstrument platform usage and productivity metrics to measure whether investments are moving the needle\nCollaboration & Growing Others\nParticipate in design discussions and code reviews; give and receive feedback constructively\nMentor other engineers on the team\nContribute to documentation and onboarding materials that reduce tribal knowledge\nQualifications: Knowledge, Skills, and Abilities\nRequired\n5+ years of professional software engineering experience, delivering features and infrastructure independently in production\nHands-on experience building and maintaining CI/CD systems at org scale, preferably GitLab CI and/or Jenkins\nExperience building developer-facing tooling or platform services other engineers depend on\nHands-on experience with LLM developer tooling: MCP, LLM APIs, agent orchestration, or AI harnesses (Claude Code, Cursor, Copilot Workspace, or equivalent)\nDeep proficiency in Python or TypeScript, with production experience sufficient to own and deliver real features\nProficiency with Kubernetes and Helm at production scale on AWS or Azure\nExperience designing shared pipeline abstractions and CI/CD infrastructure used by multiple teams\nFamiliarity with infrastructure-as-code tools (Terraform, Pulumi, or equivalent)\nProficiency with standard development tooling: Git, Docker, automated testing, and modern scripting languages\nActive daily use of AI-assisted development tools\nBachelor's degree in Computer Science, Software Engineering, or equivalent experience\nPreferred\nPrior Engineering Enablement, Platform Engineering, or Developer Productivity role with direct measurement of developer velocity\nExperience building MCP servers or tool-integration layers for LLM-based systems\nExperience building or operating infrastructure for autonomous AI agents: sandboxed execution, scheduling, observability, cost management\nFamiliarity with DORA metrics and developer productivity instrumentation\nExperience with JFrog Artifactory, Nexus, or equivalent artifact management systems\nPrior experience in financial services, fintech, or a regulated technology environment\nExposure to SOC 2 or similar compliance frameworks from an engineering perspective\nWhat Success Looks Like\nWithin the first few months, a successful hire is shipping CI/CD improvements teams are actively using and contributing meaningfully to the AI tooling platform. Over time, success is adoption: more teams on shared infrastructure, faster delivery, less one-off tooling being built in isolation. Engineers who thrive here care about making other people more productive and find genuine satisfaction in watching adoption metrics climb.\nCompensation Range: $150K - $190K\nApply for this Job","company":"Meridianlink","rawCompany":"meridianlink","city":"Remote","state":"OR","isRemote":false,"isActive":false,"createdAt":"2026-08-03T14:51:05.233Z","occupations":[{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"},{"code":"15-1299.08","title":"Computer Systems Engineers/Architects","slug":"computer-systems-engineers-architects"},{"code":"17-2199.00","title":"Engineers, All Other","slug":"engineers-all-other"}],"industries":[{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"},{"code":"513210","title":"Software Publishers","slug":"software-publishers"},{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Sr. Software Engineer - Engineering Enablement","description":"Location\nUS Remote\nEmployment Type\nFull time\nLocation Type\nRemote\nDepartment\nResearch & Development\nCompensation\n$150K – $190K\nMeridianLink runs a comprehensive background check, credit check, and drug test as part of our offer process.\nIt is not typical for offers to be made at or near the top of the salary range. The actual salary will be determined based on experience and other job-related factors permitted by law including geographical location.\nMeridianlink offers:\nInsurance coverage (medical, dental, vision, life, and disability)\nFlexible paid time off\nPaid holidays\n401(k) plan with company match\nRemote work\nAll compensation and benefits are subject to the terms and conditions of the underlying plans or programs, as applicable and as may be amended, terminated, or superseded from time to time.\n#LI-REMOTE\n\nPosition Summary\nThis is a senior-level individual contributor on the Engineering Enablement team. The team builds the shared CI/CD infrastructure, AI development tooling, and sandbox environments that hundreds of R&D engineers depend on. A core part of that mission is advancing MeridianLink's AI-native development program — building the harnesses, agent infrastructure, and shared tooling that move engineering teams from ad-hoc AI usage toward autonomous, repeatable development pipelines. This role owns a significant chunk of that platform and drives adoption across engineering teams.\nThis is a hands-on role: real code, real infrastructure, direct engagement with engineering teams. The measure of success is how much faster you make everyone else.\nKey Competencies\nWhat it means to be a Senior Engineer at MeridianLink\nSenior individual contributors own their work end-to-end, identify problems before they're surfaced, and make the engineers around them better. Senior engineers at MeridianLink are active, daily users of AI-assisted development tools.\nTechnical Execution & Delivery\nOwns features and infrastructure end-to-end: design through production release, limited guidance required\nIdentifies edge cases and failure modes independently within assigned scope\nParticipates actively in code review with constructive, specific feedback\nSurfaces blockers early rather than waiting for check-ins\nCraft & Professionalism\nWrites tests that catch regressions without over-engineering the suite\nMonitors shipped work, responds to issues, and follows incidents to resolution\nPuts institutional knowledge into shared systems rather than individual heads\nCI/CD & Build Systems\nDesigns pipeline abstractions (templates, shared jobs, reusable configs) that work across multiple teams and tech stacks\nReasons clearly about the tradeoffs between standardization and flexibility at org scale\nKeeps pipelines healthy, observable, and continuously improving\nAI Tooling & Developer Infrastructure\nBuilds and maintains shared MCP servers, agent orchestration harnesses, and reusable skills and plugins\nUnderstands LLM developer tooling in practice: tool definitions, agent loops, prompt management\nDesigns shared tooling with product thinking: requirements gathering, feedback triage, prioritized backlog\nSandbox & Agent Infrastructure\nOwns the shared infrastructure layer for autonomous AI agent environments: orchestration, provisioning, observability, cost controls, and security guardrails\nPartners with product teams on their individual sandbox configs while maintaining the platform underneath\nEnablement & Engineering Advocacy\nTreats engineers as customers: office hours, documentation, feedback loops\nMeasures platform impact with DORA metrics, adoption rates, and time-to-productivity data\nCloses the gap between shipping tooling and driving adoption\nExpected Duties\nCI/CD Platform\nOwn and evolve shared infrastructure: templates, shared jobs, abstractions, and standards across R&D\nResolve systemic reliability issues: flaky tests, slow builds, caching inefficiencies\nPartner with teams during migrations and help them adopt shared abstractions without disrupting delivery\nAI Tooling Platform\nBuild and maintain shared MCP server infrastructure connecting AI harnesses to internal systems (Jira, Confluence, GitLab, internal APIs)\nDevelop agent orchestration infrastructure: scheduling, observability, cost controls, security boundaries\nBuild reusable harness skills, slash commands, and workflow scripts that ship as internal plugins\nSandbox Infrastructure\nOwn the shared infrastructure for AI agent sandbox environments: container orchestration, environment templates, networking, resource management\nBuild and maintain orchestration and admin tooling: provisioning, lifecycle management, health monitoring, cost tracking\nImplement security guardrails for data isolation between sandbox environments\nEnablement & Adoption\nDrive AI tooling adoption through documentation, onboarding programs, office hours, and direct team engagement\nMaintain the internal best practices hub and AI development playbook\nInstrument platform usage and productivity metrics to measure whether investments are moving the needle\nCollaboration & Growing Others\nParticipate in design discussions and code reviews; give and receive feedback constructively\nMentor other engineers on the team\nContribute to documentation and onboarding materials that reduce tribal knowledge\nQualifications: Knowledge, Skills, and Abilities\nRequired\n5+ years of professional software engineering experience, delivering features and infrastructure independently in production\nHands-on experience building and maintaining CI/CD systems at org scale, preferably GitLab CI and/or Jenkins\nExperience building developer-facing tooling or platform services other engineers depend on\nHands-on experience with LLM developer tooling: MCP, LLM APIs, agent orchestration, or AI harnesses (Claude Code, Cursor, Copilot Workspace, or equivalent)\nDeep proficiency in Python or TypeScript, with production experience sufficient to own and deliver real features\nProficiency with Kubernetes and Helm at production scale on AWS or Azure\nExperience designing shared pipeline abstractions and CI/CD infrastructure used by multiple teams\nFamiliarity with infrastructure-as-code tools (Terraform, Pulumi, or equivalent)\nProficiency with standard development tooling: Git, Docker, automated testing, and modern scripting languages\nActive daily use of AI-assisted development tools\nBachelor's degree in Computer Science, Software Engineering, or equivalent experience\nPreferred\nPrior Engineering Enablement, Platform Engineering, or Developer Productivity role with direct measurement of developer velocity\nExperience building MCP servers or tool-integration layers for LLM-based systems\nExperience building or operating infrastructure for autonomous AI agents: sandboxed execution, scheduling, observability, cost management\nFamiliarity with DORA metrics and developer productivity instrumentation\nExperience with JFrog Artifactory, Nexus, or equivalent artifact management systems\nPrior experience in financial services, fintech, or a regulated technology environment\nExposure to SOC 2 or similar compliance frameworks from an engineering perspective\nWhat Success Looks Like\nWithin the first few months, a successful hire is shipping CI/CD improvements teams are actively using and contributing meaningfully to the AI tooling platform. Over time, success is adoption: more teams on shared infrastructure, faster delivery, less one-off tooling being built in isolation. Engineers who thrive here care about making other people more productive and find genuine satisfaction in watching adoption metrics climb.\nCompensation Range: $150K - $190K\nApply for this Job","datePosted":"2026-08-03T14:51:05.233Z","dateModified":"2026-08-03T14:51:05.233Z","hiringOrganization":{"@type":"Organization","name":"Meridianlink","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Remote","addressRegion":"OR","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"aa7a23776e43e7522ef5885a"},"url":"https://jobsearcher.com/jobs/aa7a23776e43e7522ef5885a"}}