[Hiring] AI Operations Engineer @ClickHouse

Role Description

We are looking for an AI Ops Engineer to help build and run a new AI Ops function at ClickHouse. You will work under a Technical Lead to design, build, and maintain AI-driven solutions across the business (People, Finance, Legal, and beyond) and engineering — building integrations, maintaining agents, supporting cost visibility, and helping train the org on AI best practices. This is a hands-on execution role: you will move quickly, ship real workflows, and help the team learn what works as we centralize AI Ops for the first time.

Success

• Measurable reduction in redundant or inefficient AI tool and model spend through right-sizing, routing, and cost visibility.
• A working framework for evaluating and selecting models/tools by cost, latency, accuracy, and risk, adopted across teams.
• Agents and AI workflows built, deployed, and maintained cross-functionally (People, Finance, Legal, Engineering, and beyond).
• Improved AI fluency and literacy org-wide, measured through training participation, adoption of approved tools, and reduced shadow-AI usage.
• Established identity, access, audit, and lifecycle practices for AI agents that satisfy Security and GRC requirements.

You Will

• Build AI-Powered Solutions
  • Develop and deploy solutions using LLMs, automation frameworks, and internal tooling, for both business and engineering use cases.
  • Integrate AI into existing systems (HRIS, ATS, ERP, procurement orchestration, ticketing, CI/CD, developer tooling) and legal infrastructure like CLM or Matter Management.
  • Build workflows such as document generation, data extraction, knowledge retrieval, and decision support across systems and knowledge bases.
  • Use modern integration standards (e.g., MCP) to give AI models and agents direct, secure access to internal knowledge and context.
• Support Model Evaluation
  • Help test and benchmark AI models against accuracy, latency, cost, and safety criteria.
  • Support model risk assessments and due diligence alongside Security and GRC.
  • Help implement and maintain the internal model routing solution.
• Support Cost Visibility
  • Help build dashboards and reporting for AI/LLM spend across teams and tools.
  • Implement tagging, monitoring, and alerting for cost anomalies.
  • Identify and execute on cost-optimization opportunities (prompt efficiency, caching, model right-sizing).
• Maintain Agent Infrastructure
  • Help provision, credential, and de-provision AI agent access.
  • Support deployment, versioning, monitoring, and retirement of agents.
  • Maintain and patch agent infrastructure and dependencies.
  • Help maintain audit trails and logging for agent actions.
• Deliver Training and Enablement
  • Design and deliver company-wide AI training programs tailored to different audiences — non-technical business users through engineers.
  • Create lightweight playbooks, guides, templates, and reusable components for safe, effective AI adoption.
  • Run onboarding sessions, office hours, and workshops to build AI fluency and drive adoption of approved tools and agents.
  • Establish a feedback loop with users to continuously improve training content, tooling, and documentation.

Qualifications

• 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, including trade-offs between cost, latency, and quality.
• Comfort working with usage and billing data to build cost visibility, forecasting, or optimization.
• Ability to understand both business and engineering workflows and translate them into technical solutions.
• Experience working with or integrating business systems as well as 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/non-human actors.

Compensation

The typical starting salary for this role in the US is $170,000 — $220,000 USD. The typical starting salary for this role in US Premium Markets is $200,000 — $250,000 USD.

Perks

• Flexible work environment - ClickHouse is a globally distributed company and remote-friendly. We currently operate in over 20 countries.
• Healthcare - Employer contributions towards your healthcare.
• Equity in the company - Every new team member who joins our company receives stock options.
• Time off - Flexible time off in the US, generous entitlement in other countries.
• A $500 Home office setup if you’re a remote employee.
• Global Gatherings - We believe in the power of in-person connection and offer opportunities to engage with colleagues at company-wide offsites.
• Culture - As part of a rapidly scaling start up, you will be instrumental in shaping our culture.