AI Operations Engineer

This is a fully remote position, open to applicants in United States.

📋 Description

• Develop and implement AI-driven solutions utilizing LLMs, automation frameworks, and proprietary tools.

• Integrate AI technologies with HRIS, ATS, ERP, procurement orchestration, ticketing systems, CI/CD, developer tools, CLM, and Matter Management systems.

• Create workflows for document generation, data extraction, knowledge retrieval, and decision support.

• Employ modern integration standards such as MCP to ensure secure access to internal knowledge and context.

• Evaluate and test AI models for accuracy, latency, cost, and safety.

• Assist in model risk assessments and due diligence in collaboration with Security and GRC.

• Implement and manage internal model routing solutions.

• Develop dashboards and reporting for AI/LLM expenditure.

• Establish cost tagging, monitoring, and anomaly detection systems.

• Drive cost optimization through prompt efficiency, caching, and model right-sizing.

• Provision, credential, de-provision, deploy, version, monitor, patch, and retire AI agents and infrastructure.

• Maintain audit trails and logging for agent activities.

• Design and deliver comprehensive AI training programs across the company.

• Produce playbooks, guides, templates, and reusable components to support safe AI adoption.

• Conduct onboarding sessions, office hours, and workshops.

• Establish feedback mechanisms to enhance training, tooling, and documentation.

• Work under a Technical Lead and report to the IT Business Systems Manager within the IT Operations AI Engineering function.

⛳️ Requirements

• Proven experience in building with contemporary AI/ML tools and frameworks.

• Demonstrated experience in developing and consuming APIs, building data pipelines, and architecting system integrations.

• Proficiency with cloud infrastructure, such as AWS, GCP, or Azure.

• Experience in hosting or managing services in a production environment.

• Ability to compare and assess AI models across different providers, considering cost, latency, and quality trade-offs.

• Comfortable working with usage and billing data for cost visibility, forecasting, or optimization.

• Capable of understanding business and engineering workflows and converting them into technical solutions.

• Experience working with or integrating business systems and engineering/developer tools.

• Skilled in creating training materials, documentation, or workshops suitable for both technical and non-technical audiences.

• Knowledge of data privacy, security, and compliance considerations.

• Experience in implementing AI safeguards, including identity and access controls for automated or non-human actors.

🏝️ Benefits

• Employer contributions towards healthcare.

• Equity in the company; stock options available for every new team member.

• Flexible time off policies in the US.

• Generous time-off entitlements for employees in other countries.

• A USD$500 allowance for home office setup for remote employees.

• Opportunities for global company-wide offsites and in-person connections.

• A flexible work environment.

• Remote-friendly work arrangements.