Enterprise AI Systems Engineer

Juul Labs's mission is to transition the world’s billion adult smokers away from combustible cigarettes, eliminate their use, and combat underage usage of our products. We have the opportunity to address one of the world’s most intractable challenges through a commitment to exceptional quality, research, design, and innovation. Backed by leading technology investors, we are committed to the same excellence when it comes to hiring great talent.

We are a diverse team that is united by this common purpose and we are hiring the world’s best engineers, scientists, designers, product managers, operations experts, and customer service and business professionals. If the opportunity to build your career is compelling, read on for more details.

• →You own these platforms end to end. What you build gets used across the whole company, and you decide how AI runs here rather than inheriting someone else's design.
• →Administer our enterprise Claude, Gemini, OpenRouter, Cursor and NotebookLM tenants. User provisioning, groups and roles, workspace configuration, and tenant security settings.
• →Build and maintain the content that makes those platforms useful: skills, prompts, projects, connectors, and the documentation behind them. Drive adoption across 250 users and growing.
• →Track consumption and spend across all three platforms. Report on usage, find idle seats, and support the business-unit chargeback model.
• →Keep the platforms running. Availability monitoring, feature rollouts, user issue triage, and escalation ownership when something breaks.
• →Build and operate the MCP servers and gateways that connect these platforms to internal systems, with least-privilege access and full audit logging.
• →Run the LLM gateway that centralizes routing, authentication, rate limiting, logging, and policy enforcement across model providers.
• →Choose the right model for each workload, commercial or open-weight, based on cost, latency, capability, and how sensitive the data is.
• →Build agentic workflows and automations against internal APIs and tools, with the evaluation and guardrails to keep them predictable.
• →Architect and run AI workloads on AWS and GCP: compute, networking, IAM, secrets management, private connectivity, Bedrock, and Vertex AI.
• →Own the code in GitHub and write most of it yourself, mostly Python and TypeScript. Branch protection, access control, secret scanning, and Actions pipelines.
• →Instrument the stack for cost, performance, and security telemetry, and build the reporting that leadership and finance rely on.
• →Enforce data handling, retention, and access policy alongside Cybersecurity and AI Governance, and write the runbooks and standards behind it.
• →Perform related duties as assigned, within your scope of practice 

• 5+ years in software, cloud, or platform engineering, including recent hands-on work building and running LLM-based systems.
• Experience administering an enterprise SaaS or AI tenant at scale: access management, configuration, cost control, and adoption.
• Working knowledge of both commercial and open-weight LLMs, including prompt engineering, evaluation, retrieval, and agentic patterns.
• Hands-on with Model Context Protocol (MCP), MCP gateways, or LLM gateways. Comparable API integration and middleware experience counts.
• AWS and GCP architecture, including IAM, networking, secrets management, and managed AI services.
• GitHub and standard engineering discipline: version control, code review, testing, CI/CD, and infrastructure as code.
• Strong Python and/or JavaScript/TypeScript for building integrations, automations, and internal tooling.
• Security and data governance fundamentals applied to AI work: least privilege, data classification, DLP, and auditability.
• Able to explain technical work to executives, finance, and people who do not work in technology.
• Nice to have: Vertex AI or Amazon Bedrock, self-hosted open-weight model deployment, vector databases and RAG pipelines, Splunk or another SIEM, and cloud cost management.

• Preferred, bachelor degree in applicable field or relevant work experience