LLM Ops Engineer

Litera

Last Updated: 8/22/2026 12:08:35 AM

Live Market Data for this Exact Role

These metrics reveal the true, unfiltered history of this specific position. We track the exact number of days the requisition has been active and monitor real salary range fluctuations over time, helping you verify compensation trends before applying.

Current Days Open
25
Reqs Seen
1
Current Min Salary
$105,000.00 (Yearly)
Current Max Salary
$130,000.00 (Yearly)
Historical Time to Fill
N/A
First Seen
7/29/2026
Lowest Min Salary Seen
$105,000.00 (Yearly)
8/22/2026
Highest Max Salary Seen
$130,000.00 (Yearly)
8/22/2026

Full Job Description

Job Description Ready to Help Shape the Future of Legal Tech?! At Litera, we dont just build software, we transform how the worlds top law firms operate. Every day, we RaiseTheBar for whats possible through AI, innovation, and solutions that power millions of legal professionals worldwide. If youre energized by scale, real impact, and meaningful challenges, youll feel right at home here. Where Youll Work This is a hybrid role based in Denver, CO with the expectations to be in office at least 3 days a week for collaboration and connection. Why this Role Matters At Litera, AI is becoming a critical enabler of how we build products, improve customer experiences, and drive innovation. As an LLM Ops Engineer, you will create the secure, scalable, and reliable foundation that allows our engineering teams to leverage AI confidently and efficiently across the business. Your work will ensure that AI capabilities are available, governed, cost-effective, and ready to support production applications at scale. This role is instrumental in accelerating AI adoption while maintaining the performance, security, and resilience required for enterprise software. What Youll Deliver Build and operate a scalable AI platform that enables engineering teams to seamlessly access and deploy models across multiple providers and environments. Ensure high availability and resiliency of AI services through intelligent routing, failover strategies, and production-grade infrastructure. Establish secure and compliant AI operations by protecting model access, safeguarding sensitive data, and enforcing governance standards. Create a consistent developer experience through unified APIs, self-service capabilities, tooling, and best practices that accelerate AI adoption. Optimize AI platform performance, reliability, and cost efficiency through proactive monitoring, analytics, and provider strategy management. Lead the evolution of Literas AI operations capabilities by evaluating emerging technologies and recommending scalable solutions. Deliver observability and operational excellence through dashboards, alerting, quality monitoring, and service-level metrics. Support the safe deployment of AI solutions by implementing testing frameworks, quality controls, and production readiness standards. Were committed to creating an inclusive environment. If you need accommodations at any point in the process or in the role, were here to support you. What Youll Bring Must-Haves: 3+ years of experience in DevOps, Platform Engineering, MLOps, or a related field, including hands-on experience operating LLMs in production environments. Experience deploying, managing, and scaling models across multiple AI providers such as OpenAI, Anthropic, Azure OpenAI, AWS Bedrock, or Google Vertex AI. Strong expertise in building highly available, secure infrastructure, including load balancing, failover strategies, secrets management, and access controls. Experience with API management, gateway technologies, and production-grade AI service operations. Strong Python programming skills with experience developing and supporting scalable systems. Proven ability to solve complex technical challenges and thrive in a fast-paced, evolving environment while collaborating across teams. Nice to Haves: Experience fine-tuning or training large language models for domain-specific applications. Familiarity with ML orchestration tools and frameworks such as Kubeflow, MLflow, or Apache Airflow. Experience with LLM evaluation frameworks, retrieval-augmented generation (RAG), vector databases, or inference optimization techniques. Knowledge of infrastructure-as-code, Kubernetes, compliance frameworks, or large-scale AI cost optimization strategies. We know great candidates dont always check every box. If youre excited about this role, we encourage you to apply. What Youll Experience A team that shows up. Work alongside people who collaborate, support one another, and lead with integrity. Global Reach. Partner with teams around the world to solve complex challenges that matter. Real opportunity for growth. Expand your impact through meaningful stretch opportunities, visibility and career development. AI-driven innovation. Work at the intersection of legal technology, customer outcomes, and cutting-edge AI. Pay Transparency for Colorado Applicants The base salary range for this role is $105,000 to $130,000 USD. Final compensation will be determined based on experience, skills, education, and other relevant qualifications. This role is also eligible to participate in a company bonus plan. In addition to base salary, Litera offers a comprehensive benefits package, including medical, dental, and vision coverage, a 401(k) with company match, and incentive and recognition programs. Benefits are subject to eligibility requirements. #LI-Hybrid Litera is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. Litera is a fast-growing software company and one of the leading legal technology suppliers in the world. Serving more than 90% of the world's largest law firms, our software is used by hundreds of thousands of lawyers every day. As a company recognized as one of the best places to work, we believe professional development, rewards programs, open communication, and transparent leadership all contribute to a unique and open work environment. Our employees are driven, energetic, passionate, and have the ability to make a direct impact on the future of the company.

Similarity vs. Compensation Matrix

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