# Senior Manager, AI Corporate Engineering

**Company:** [Vanta](https://hotfix.jobs/companies/vanta)
**Location:** Remote
**Role:** Engineering Management
**Salary:** $210k – $247k/yr
**Experience:** 8+ years
**Skills:** ai platform engineering, llm tooling, mcp, OAuth, identity and access management, CI/CD, Infrastructure As Code, cost attribution, token economics, agent architecture, Data Governance, Technical Program Management
**Posted:** 2026-08-10

> Leads a senior team building Vanta’s internal AI platform, including access controls, MCP infrastructure, cost governance, application deployment patterns, and enablement. Requires 8+ years in platform, infrastructure, or systems engineering and 3+ years managing engineers.

## Job Description

## Responsibilities
- Lead, coach, and grow a senior team spanning platform engineering and technical program management.
- Own identity and authentication for AI tools, connector and integration allowlisting, tiered permissions, and secure-by-default guardrails.
- Build AI cost engineering capabilities, including team- and individual-level attribution, model right-sizing, agent and automation spend traceability, budget thresholds, and alerting.
- Own the internal MCP layer, including commissioning, decommissioning, governance, and downstream impact assessments.
- Establish a golden-path deployment pattern for internal applications with private-by-default settings, lifecycle policies, and build-versus-buy guidance.
- Build enablement capabilities, including a skills and agent registry, an evaluation framework for internal AI usage, and technical enablement on sanctioned tools.
- Define the Corporate Engineering charter, ownership boundaries, intake process, and roadmap.
- Coordinate cross-functional work across Engineering, GRC, Security, Data, Finance, and People.
- Operate through influence across partner organizations and help non-developers safely build internal tools.

## Requirements
- Experience standing up an internal AI or developer platform function from the ground up.
- Ability to define scope, deliver bounded first versions, and manage commitments and priorities.
- Fluency in AI cost engineering, including usage attribution, model right-sizing, token economics, agent cost traceability, limits, and guardrails.
- Hands-on technical depth across LLM platform tooling, agent and MCP architecture, identity and OAuth, CI/CD, and infrastructure as code.
- Understanding of data governance in regulated environments and responsible handling of sensitive data in prompts, repositories, and third-party tools.
- Comfort operating through influence across product AI, security policy, data platform, and budget teams.
- 8+ years in platform, infrastructure, or systems engineering.
- 3+ years managing and developing engineers.
- Authorization to work in the U.S. without current or future employer sponsorship.
- Curiosity and sound judgment in using AI responsibly to improve efficiency and impact.

## Compensation and Benefits
- Industry-competitive salary and equity.
- Comprehensive medical, dental, and vision coverage, with employee-only premiums covered for most medical plans.
- 16 weeks of paid parental leave for all new parents.
- Health and wellness stipend.
- Remote workspace, internet, and cellphone stipends.
- Commuter benefits for team members reporting to the San Francisco and New York City offices.
- Family planning benefits.
- Matching 401(k) contribution with immediate vesting.
- Flexible paid time off and 80 hours of sick time.
- 11 company-paid holidays.
- Virtual team-building activities, lunch-and-learns, and company-wide events.

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