AI Operations Engineer

About the job

Responsibilities

• Develop and deploy AI-powered solutions using LLMs, automation frameworks, and internal tooling for business and engineering use cases.
• Integrate AI into existing systems such as HRIS, ATS, ERP, procurement, ticketing, CI/CD, developer tooling, and legal infrastructure.
• Build workflows for document generation, data extraction, knowledge retrieval, and decision support.
• Utilize modern integration standards to provide AI models and agents secure access to internal knowledge.
• Test and benchmark AI models based on accuracy, latency, cost, and safety criteria.
• Support model risk assessments and due diligence with Security and GRC teams.
• Implement and maintain the internal model routing solution.
• Build dashboards and reporting for AI/LLM spend, and implement cost monitoring and alerting.
• Identify and execute cost-optimization opportunities, including prompt efficiency, caching, and model right-sizing.
• Provision, credential, and de-provision AI agent access.
• Support the deployment, versioning, monitoring, and retirement of AI agents.
• Maintain and patch agent infrastructure and dependencies, including audit trails and logging.
• Design and deliver company-wide AI training programs for diverse audiences.
• Create playbooks, guides, and templates for safe and effective AI adoption.
• Conduct onboarding sessions, office hours, and workshops to enhance AI fluency and tool adoption.
• Establish a feedback loop to continuously improve training content, tooling, and documentation.

Requirements

• Experience building with modern AI/ML tools and frameworks.
• Experience building and consuming APIs, developing data pipelines, and architecting system integrations.
• Working knowledge of cloud infrastructure (AWS, GCP, or Azure) and experience hosting or operating services in production.
• Experience comparing and evaluating AI models across providers, considering trade-offs in cost, latency, and quality.
• Comfort working with usage and billing data for cost visibility, forecasting, or optimization.
• Ability to understand business and engineering workflows and translate them into technical solutions.
• Experience working with or integrating business systems and engineering/developer tooling.
• Experience creating training materials, documentation, or workshops for mixed technical/non-technical audiences.
• Understanding of data privacy, security, and compliance considerations.
• Experience implementing safeguards in AI systems, including identity and access controls for automated actors.

Benefits

• Flexible work environment - globally distributed and remote-friendly.
• Employer contributions towards healthcare.
• Equity in the company (stock options).
• Flexible time off in the US, generous entitlement in other countries.
• USD$500 Home office setup for remote employees.
• Opportunities to engage with colleagues at company-wide offsites.