Senior Legal AI Platform Engineer
- Status
- Open
- Remote policy
- Remote
- Employment type
- Not stated
- Salary
- 100,000-150,000 USD / year
- Categories
- Legal
- Source
- cribl
- First observed
- 2026-09-09 19:55 UTC
- Last seen
- 2026-09-09 19:55 UTC
- Source claims posted
- 2026-09-09 16:20 UTC
- Consecutive misses
- 0 of 3
What the posting says
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 fastest‑growing private companies and a leading player in a massive, fast‑moving market. With a global workforce, we’re remote‑first 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
The Senior Legal AI Platform Engineer is the builder and architect inside that model—turning requirements, contract logic, risk tolerances, and service design into durable workflows, integrations, automations, agents, and technical controls. This is the administration of Legal-specific platform delivery and partners with LITS AI (Legal, IT, Security) platform engineering team and Enterprise Applications on shared infrastructure and standards.The core need is focused, high-context technical ownership: someone who can translate legal and commercial requirements across CLM, CRM, clickwrap, intake, approvals, evidence, reporting, and AI-enabled workflows into observable, governed production systems. The roadmap includes AI plugins and single-job agents, privacy software implementation, CRM | CLM continuity, denied-party integrations, product and partner clickwrap, CLM infrastructure, data & security pipelines | lakes | observability, HR contract workflows, content and routing distribution, system documentation alignment, and broader AI and intelligence enablement.
You’ll own the technical implementation and operation of that work while preserving the decision rights of the lawyers, privacy professionals, security partners, and business owners responsible for the underlying requirements. Do this well and the wins stack up fast: less manual work, more service scale, higher automation quality, tighter governance, and one less bottleneck choking the LITS AI Legal roadmap. What you leave behind is a durable Legal runtime—not a collection of one-off automations, thin integrations, or undocumented administration.
As An Active Member Of Our Team, You Will…
Independently own Legal AI systems and components from requirements and technical design through implementation, testing, release, operation, and documentation.
Architect and operate integrations across CLM | CRM, intake, workflow, knowledge, identity, and collaboration systems using APIs, webhooks, queues, automation platforms, and reliable data contracts.
Turn approved legal language, routing rules, risk thresholds, and conditioned paths into maintainable technical controls while preserving required HITL review and escalation.
Build governed AI plugins, single-job agents, and automations that consume approved source content without duplicating or forking it across tools.
Develop evaluation and quality controls, including representative test sets, regression checks, schema validation, traceability, and evidence showing when system behavior changes.
Instrument the stack for reliability, auditability, model and vendor cost, and operational telemetry—feeding decision-making with high-quality data.
Apply production controls for SSO/SCIM, service identities, scoped credentials, secrets management, privileged administration, access, logging, monitoring, incident handling, and rollback.
Maintain automated tests, CI/CD workflows, dependency controls, release evidence, runbooks, and system maps so services remain understandable and supportable beyond any single person.
Carry systems from problem definition through production, then establish the operating owner, maintenance model, and handoff SLA appropriate to each system.
Partner on workflow and playbook design, reliability, cost, value signals, usability, adoption, and feedback.
Own the technical delivery required for contracting, clickwrap, denied-party screening, privacy operations, and HR contract workflows without taking ownership away from the relevant domain lead.
Improve self-service and low-touch contracting by encoding approved language, conditions, routing, and review gates into contract-generation and review systems.
Partner with Legal AI Analysts and Legal stakeholders as the SME counterpart to operational design—using service pain points, process observations, and user feedback to resolve issues in system behavior, data quality, usability, and adoption.
Support reporting, data modeling, and operational telemetry covering automation rates, cycle times, ticket reduction, roadmap progress, satisfaction, budgeting, and broader business impact.
Keep the boundary between shared infrastructure and Legal-specific delivery explicit, using common platform capabilities where they fit and building Legal-owned solutions where distinct requirements or elevated risk justify them.
Act as a role model and technical mentor for others in role execution, and cross-functional collaboration.
Work effectively across a remote-first company and multiple time zones, including occasional work outside standard hours when production needs require it.
If You’ve Got It - We Want It
Seasoned experience in software, platform, integration, or infrastructure engineering, with independent ownership of complex production systems or components.
Hands-on ability with a general-purpose programming language such as Python, along with APIs, webhooks, structured data, automation, and systems troubleshooting.
Experience with cloud services, event-driven architectures, queues, containers, source control, CI/CD, automated testing, release controls, and production observability.
Practical experience with AI/LLM systems, including model APIs, retrieval or tool-use patterns, agents, evaluation, HITL controls, and the limits of generative output.
Strong identity and security fundamentals, including OAuth, service identities, least-privilege access, SSO/SCIM, secrets management, audit logging, and secure operational practices.
End-to-end technical ownership of CLM, CRM, workflow, service-desk, spend-management, repository, or adjacent operational platforms—from architecture through maintenance, not only configuration at the margins.
Strong systems thinking and data judgment, including the ability to translate legal, contractual, compliance, and policy requirements into workflows, fields, conditions, repositories, technical controls, and auditable evidence.
Good judgment in selecting the methods and techniques used to build solutions.
Demonstrated ability to investigate ambiguous problems, prioritize across multiple initiatives, and turn partially defined operational needs into shipped, maintainable outcomes with limited day-to-day direction.
Excellent communication and change-management skills across engineers, lawyers, analysts, security partners, finance stakeholders, People teams, and business-system owners.
The ability to advocate firmly for core convictions while remaining adaptable and keeping scope, ownership, and tradeoffs clear.
Experience with AI governance, privacy, information governance, or legal knowledge systems, particularly where the work requires balancing enablement with control.
Comfort working with reporting, metrics, dashboards, and BI-adjacent outputs that help Legal understand operational performance and communicate value.
A strong bias toward simple architecture, durable systems of record, measurable operation, clean documentation, and scalable operating patterns—not heroics, one-off fixes, or undocumented admin work.
Experience with AWS serverless services, containerized workloads, GitHub Actions, MCP or other tool-use integrations, and production AI evaluation is a strong plus.
#LI-KJ1
#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
$100,000—$150,000 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 cribl.io/about-us.
Quality
- + Salary range stated weight 35%
- + Remote policy stated weight 20%
- + Location stated weight 15%
- + Organisation stated weight 15%
- + Publication date stated weight 15%
Not enough history yet to judge honesty signals.
Timeline
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#663147 2026-09-09 19:55 UTCPublished