Senior LLM Ops Engineer

Remote • Posted 1 day ago • Updated 4 hours ago
Full Time
Remote
Fitment

Dice Job Match Score™

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Job Details

Skills

  • Accounting
  • Management
  • SaaS
  • SAFE
  • Large Language Models (LLMs)
  • System Integration Testing
  • Cost Control
  • Research
  • Production Engineering
  • Cost Management
  • Budget
  • Caching
  • Optimization
  • Privacy
  • Mentorship
  • Software Engineering
  • DevOps
  • Orchestration
  • Evaluation
  • Performance Tuning
  • Cloud Computing
  • Workflow
  • Leadership
  • Collaboration
  • Problem Solving
  • Conflict Resolution
  • FOCUS
  • Artificial Intelligence

Summary

Senior LLMOps Engineer (Remote - Global - Work From Anywhere)

About CINC Systems

CINC Systems is the leading provider of accounting and management software for the community association management industry. Our platform supports tens of thousands of associations and millions of homes, operating in a highly regulated, data-sensitive, multi-tenant SaaS environment.

We are building AI-native capabilities into the core of our platform, not as experiments, but as reliable, scalable systems that deliver real value to customers. The Senior LLMOps Engineer plays a critical role in making AI production-ready, observable, safe, and cost-effective.

About the Role
The Senior LLMOps Engineer is a hands-on technical leader responsible for operating, scaling, and governing large language model capabilities across the CINC platform. This role focuses on the systems and practices that sit between AI engineering and production operations: orchestration, evaluation, observability, safety, and cost control.
This is not a research role. It is a production engineering role for someone who understands that AI systems must be treated like any other critical software system, with strong fundamentals, clear feedback loops, and disciplined operations.

Key Responsibilities
Design and operate LLM orchestration and runtime systems that support reliable, low-latency AI workflows
Build and maintain evaluation pipelines to measure quality, regressions, and business impact of LLM-driven features
Implement observability for AI systems, including tracing, metrics, and feedback loops at the prompt, agent, and workflow levels
Establish cost management strategies for LLM usage, including budgeting, rate limiting, caching, and optimization
Partner with AI and product engineers to productionize AI features safely and incrementally
Define and enforce guardrails for security, privacy, and data handling in AI workflows
Support experimentation with new models and tools while ensuring production stability
Improve incident readiness and response for AI-related failures and degradations
Influence build versus buy decisions for LLM tooling and platforms
Mentor engineers and help establish best practices for operating AI systems at scale

Qualifications

Technical Experience
8+ years of experience in software engineering, platform engineering, or DevOps roles
Hands-on experience operating LLM-powered systems in production
Familiarity with LLM providers and orchestration frameworks
Strong understanding of distributed systems, APIs, and cloud-native architectures
Experience designing observability and evaluation systems for complex workflows
Practical knowledge of cost and performance optimization in cloud environments
Experience working with event-driven architectures and asynchronous workflows

Leadership and Collaboration
Proven ability to lead through influence rather than authority
Highly structured thinker with strong problem-solving skills
Clear communicator capable of explaining AI operational trade-offs to technical and non-technical stakeholders
Comfortable working across teams in a fast-moving, evolving environment

Mindset and Values
Builder mindset with a focus on reliability and outcomes
Belief that AI amplifies engineering fundamentals rather than replaces them
Learning-first attitude, staying current with evolving AI tools and practices
Pragmatic and calm under pressure, especially during incidents
Customer-aware, understanding the real-world impact of AI behavior

What Success Looks Like
LLM-powered features are reliable, observable, and cost-effective in production
Engineers can ship AI-enabled capabilities with confidence and clear guardrails
AI quality and performance issues are detected early and addressed quickly
The organization develops strong operational discipline around AI systems
The Senior LLMOps Engineer is recognized as a trusted expert and partner across engineering

CINC is an Equal Opportunity Employer of women, minorities, protected veterans and individuals with disabilities.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
  • Dice Id: 80183947
  • Position Id: a2a0bcfd453d0e287ab96105a167d3c3
  • Posted 1 day ago
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