AI Operations Engineer, Americas

CodeRabbit•Boston, MA

4d•$140,000 - $180,000•Hybrid

About The Position

CodeRabbit is hiring an AI Operations Engineer to identify operational gaps in support, design solutions, and execute them end to end. The role focuses on building and deploying automation systems, AI-powered workflows, integrations, data systems, and tools that improve productivity, customer satisfaction, and support quality. The engineer will work across Product, Engineering, Services, and Support to understand pain points, while independently driving and implementing technical solutions. The position involves building support frameworks and knowledge management systems, including automated playbooks, runbooks, FAQs, and documentation. The engineer will create dashboards, metrics systems, and data pipelines, evaluate and implement the support tooling stack, and own technical initiatives from problem identification and prototyping through deployment and optimization. The role is based in San Francisco, CA or Boston, MA, with Boston preferred, and is hybrid.

Requirements

At least 3 years of hands-on experience building support operations systems, automation, or technical solutions autonomously in a SaaS environment.
A proven record of identifying operational problems and independently building and deploying solutions that measurably improve support metrics.
Strong technical foundation and proficiency in Python, JavaScript, or similar languages, with the ability to independently build automation, data systems, and dashboards and ship solutions.
Customer obsession and a commitment to delivering a high-quality customer experience.
Systems thinking: ability to identify operational gaps, architect fixes, and execute end to end independently.

Nice To Haves

Proficiency in at least one programming or scripting language.
Experience with code review processes and tools.
Familiarity with observability, root-cause analysis (RCA), and debugging practices and tools.
Strong understanding of modern software development practices, version control systems, and the software development ecosystem, such as Git, GitHub, CI/CD, VS Code, and Cursor.
Knowledge of customer success, sales, and professional services, such as retention, expansion, MEDDPICC, and services delivery.
Bachelor’s degree or equivalent in computer science, engineering, mathematics, or another technical field.

Responsibilities

Identify support operations gaps and independently design, build, and deploy automation systems and AI-powered workflows.
Build operational frameworks such as automated playbooks, process integrations, and quality systems to address support inefficiencies at scale.
Build dashboards, metrics systems, and data pipelines to reveal operational gaps and guide improvements.
Own the problem-to-solution cycle by identifying recurring issues, architecting technical fixes, and implementing automation, integrations, and tooling.
Build and own a knowledge management system, including automated runbooks, playbooks, FAQs, and documentation.
Engineer, deploy, integrate, and optimize AI-powered workflows and automation.
Evaluate, architect, and implement the support tooling stack, making independent decisions and building scalable integrations.
Own technical initiatives end to end, from problem identification and prototyping through validation, deployment, and optimization.
Build systems that improve support quality, including quality automation, specialization tooling, knowledge distribution, and training frameworks.
Identify and execute supportability improvements, partnering with Engineering and Product on AI-driven support.
Drive strategic projects to identify, implement, and scale tools and automation that improve support efficiency and customer experience and leverage LLM/AI capabilities.