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

a16z•Menlo Park, CA

27d•$221,000 - $258,000•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. The role supports teams across the firm by delivering secure, reliable systems and reducing friction through automation and self-service workflows. It involves leading complex technical deployments, managing privileged access, and serving as a technical escalation point for stakeholders. This is a hands-on position on the IT Systems team, working closely with Cybersecurity, Engineering, Product, Data, and other business units. The engineer will handle complex, ambiguous, or urgent requests and deliver solutions that are secure, well documented, and supportable. The work includes operating AWS and GCP infrastructure, supporting Databricks and cloud AI services, and helping business teams turn ideas into applications from prototype through deployment and ongoing support. The role requires working in the office three days per week in either San Francisco or Menlo Park, California. The anticipated salary range is $221,000–$258,000. The role is eligible for the a16z carry program, discretionary bonus programs, and 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 use of AI workflows, 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 shipping 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 ecosystems 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 problems across enterprise systems, infrastructure, identity, and integrations, and weigh security, reliability, cost, and user experience when choosing solutions.
Experience making production system changes with adequate testing, monitoring, and rollback plans, responding effectively when issues occur, and communicating appropriately.
Low ego and high empathy, including listening to different perspectives, questioning assumptions, and using evidence to identify effective solutions.
High agency, including taking initiative, managing priorities, navigating ambiguity, collaborating effectively, and proactively communicating progress, risks, and blockers.

Responsibilities

Own the firm's most challenging IT issues related to AI deployments, making technical decisions and building lasting solutions.
Co-own implementation of new enterprise systems and emerging AI applications, including evaluating, testing, and securely deploying capabilities at scale.
Identify opportunities to reduce manual work and build automations across the IT organization.
Partner with business teams and internal builders to develop applications from early 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, helping stakeholders resolve complex problems.
Participate in incident response and root-cause analysis to restore service and prevent future issues across enterprise systems.
Maintain documentation, runbooks, and decision records, and share knowledge to improve IT team operations.