Senior MLOps Engineer (LLMOps)

TL;DR

Senior MLOps Engineer (LLMOps): Building and scaling technical infrastructure for AI/ML systems with an accent on LLM pipelines, agentic systems, and high-performance serving. Focus on designing reusable CI/CD workflows, optimizing model performance, and implementing robust observability for production-ready AI.

Location: Remote (North America)

Salary: $200,000 - $275,000

Company

hirify.global provides AI-powered intelligence solutions to help public and private sector agencies investigate and disrupt crime using blockchain intelligence.

What you will do

• Build reusable CI/CD workflows for model training, evaluation, and deployment using Langfuse and GitHub Actions.
• Develop a modular AI infrastructure stack including vector databases, feature stores, model registries, and observability tooling.
• Continuously evaluate and integrate state-of-the-art tools like LangChain, LlamaIndex, vLLM, MLflow, and BentoML.
• Deploy infrastructure to support offline and online evaluation of LLMs and agents, including regression testing and cost monitoring.
• Ensure data accuracy, consistency, and reliability to improve model training and inferencing.
• Partner with engineering and data science teams to embed AI models and agents into real-time applications.

Requirements

• Ability to write high-quality, maintainable software, primarily in Python.
• Strong background in scalable infrastructure, including Docker, Kubernetes, and Terraform.
• Experience with monitoring and logging frameworks such as Datadog, Prometheus, or OpenTelemetry.
• Deep understanding of ML Ops best practices, including model versioning, rollback strategies, and drift detection.
• Experience deploying and maintaining LLM and agentic workflows in production.
• Must be based in North America.

Culture & Benefits

• Eligibility to participate in TRM’s equity plan.
• Distributed-first operating model with hubs in major cities like SF, NY, and London.
• High-velocity environment rewarding urgency, adaptability, and personal ownership.
• Strong emphasis on AI fluency, expecting team members to use AI to accelerate their craft.
• Mission-driven culture focused on national security and fighting crime.