Partner 20, Senior IT & AI Platform Engineer, San Francisco/Menlo Park

Andreessen Horowitz•San Francisco, CA

13d•Hybrid

About The Position

Andreessen Horowitz (a16z) is hiring a Senior IT & AI Platform Engineer to build, deploy, and operate enterprise systems, AI applications, and cloud infrastructure that help teams execute securely and efficiently. This hands-on role is part of the IT Systems team and works closely with Cybersecurity, Engineering, Product, Data, and other business units. The engineer will lead complex deployments, act as a trusted technical escalation point, manage privileged access across critical systems, and reduce friction with reliable automation and self-service workflows. Typical work may include orchestrating AI coding agents, managing AWS or GCP infrastructure, and helping a business unit deploy a custom application. The role involves complex, ambiguous, and sometimes urgent requests, with an emphasis on delivering secure, well-documented, supportable outcomes. The position requires working in the office three days per week at either the San Francisco, California, or Menlo Park, California office. The anticipated salary range is $221,000–$258,000. Actual starting pay may vary based on factors including experience, skills, and scope. The role is eligible for participation in the a16z carry program and discretionary bonus programs, as well as benefit and perquisite plans.

Requirements

At least 8 years of experience in platform engineering, systems administration, cloud infrastructure, or IT engineering, with responsibility for production systems.
Advanced AI workflow experience beyond tools such as ChatGPT/Codex, Claude Code, and Wispr Flow.
Experience transforming IT operations using AI.
Experience deploying AI applications with enterprise systems and data, including SSO, provisioning, integrations, permissions, administrative controls, and staged rollouts.
Experience taking internal applications or tools from prototype to production, including authentication, API integrations, deployment, and ongoing support.
Hands-on AWS and GCP experience, including IAM, networking, application hosting, storage, and logging, as well as infrastructure-as-code tools such as Terraform, CloudFormation, or Pulumi.
Experience administering or supporting Databricks, including workspaces, service principals, permissions, and monitoring, in partnership with data engineering teams.
Experience administering modern enterprise infrastructure and SaaS environments such as Okta, Google Workspace, Slack, GitHub, Jamf, Intune, and cloud-native environments.
Experience building maintainable automations and API integrations using code and low-code/no-code platforms, with version control, testing, monitoring, and safe deployment practices.
Ability to diagnose complex issues across enterprise systems, infrastructure, identity, and integrations, and assess security, reliability, cost, and user experience when selecting solutions.
Experience making production changes with appropriate testing, monitoring, rollback plans, and incident response, while communicating appropriately.
Low ego and high empathy, including listening to different perspectives, questioning assumptions, and using evidence to find solutions.
High agency, including taking initiative, managing priorities, navigating ambiguity, collaborating, and proactively communicating progress, risks, and blockers.

Responsibilities

Take ownership of challenging IT issues related to AI deployments and make technical decisions that deliver lasting solutions.
Co-own implementation of enterprise systems and emerging AI applications, including evaluating, testing, and securely deploying capabilities at scale.
Identify opportunities to reduce manual work and build automation across IT.
Partner with business teams and internal builders to turn ideas into applications, from prototypes through deployment, hardening, and ongoing support.
Build and operate AWS and GCP infrastructure.
Partner with Cybersecurity to protect sensitive data and manage privileged access across AI, SaaS, cloud, endpoint, and internal systems.
Support Databricks and cloud AI services, including workspace configuration, service principals, access controls, and operational monitoring.
Serve as a technical escalation point for cybersecurity, engineering, data, and other business units; help stakeholders resolve complex problems.
Participate in incident response and root-cause analysis to restore service and prevent recurring issues across enterprise systems.
Maintain documentation, runbooks, and decision records, and share knowledge to improve IT operations.