Staff Security Engineer - Enterprise AI

United States Digital Space LLC; San Francisco (CA); Hybrid; USD 204,000 - 281,000; Full time

Benefits offered by this job

Equity

Hybrid work

Medical insurance

Job summary

United States Digital Space LLC is seeking a Staff Security Engineer focused on Enterprise AI to own AI governance across the enterprise security program in San Francisco. You will partner with engineering, data, and leadership to shape secure AI adoption, governance, and scale.

You will build decision frameworks, manage AI platforms, and ensure compliance logs flow to SIEM; lead pilots end-to-end and mentor teams while staying ahead of fast-changing AI tech.

Qualifications

• 7+ years in security, platform, or infra engineering.
• Experience presenting to senior leadership.
• Ability to work independently and build stakeholder relationships.
• Strong communication across audiences, from engineers to execs.
• Proficiency in Python, Go, or Java; ability to build integrations.

Responsibilities

• Own and drive the org-wide AI strategy with governance and security focus.
• Act as technical authority for AI platform administration and risk-based enablement.
• Design scalable internal systems and experiment infrastructure for AI.
• Lead AI pilots end-to-end and ensure observability into SIEM.
• Develop adoption tracking and data pipelines with analytics teams.

Skills

Security engineering

Platform engineering

Infrastructure engineering

Communication skills

Independent work

Python

Go

Java

Tools

Datadog

Splunk

AI/LLM platforms

Job description

About the company

the company is a technology wholesale platform built on the belief that the future is local. Independent retailers around the globe collectively represent a multi-hundred-billion-dollar wholesale market that has historically been fragmented and offline. At the company, we're using the power of tech, data, and machine learning to connect this thriving community of entrepreneurs across the globe. Picture your favorite boutique in town — we help them discover the best products from around the world to sell in their stores. With the right tools and insights, we believe that we can level the playing field so businesses can grow and local communities can thrive.

We’re looking for smart, resourceful and passionate people to join us as we power the shop local movement. If you believe in community, come join ours.

About this role

The Enterprise Security team at the company owns the tools and policies that keep our people, data, and systems protected. The team's scope includes endpoint detection, data loss prevention, email security, corporate threat detection, compliance training, and AI governance. As our Staff Security Engineer focusing on Enterprise AI, you will own the AI governance domain within Enterprise Security, serving as IT's technical leader for how the company adopts, secures, and scales AI. You'll partner with engineering teams already driving AI initiatives to ensure governance, security, and enablement keep pace with adoption, working across every level of the organization.

What you'll do

• Own and drive the company's company-wide AI strategy in partnership with engineering, business, and executive stakeholders. This means setting the direction for which tools we adopt, how we govern them, and how we scale adoption.

• Serve as the technical authority on AI platform administration for tools like Anthropic and OpenAI. You'll evaluate, enable, and disable native connectors, plugins, and features based on risk, security posture, and business value.

• Build and maintain decision frameworks (e.g., risk matrices, enablement criteria) that make AI governance repeatable and transparent.

• Design and engineer secure experimentation infrastructure, including sandboxed environments, isolated MCP connectors for testing new features, and scoped OAuth flows, so teams can safely explore new AI capabilities.

• Design and build custom MCP integrations when out-of-the-box options don't exist or don't meet the company's security requirements (e.g., overly broad permissions, insufficient audit logging).

• Lead AI pilot programs end-to-end, from scoping and stakeholder alignment through rollout, troubleshooting, feedback collection, and iteration.

• Engineer observability and compliance infrastructure, ensuring compliance logs from AI platforms end up in our SIEM.

• Own the operational mechanics of AI adoption tracking. This includes automating usage data pipelines into Snowflake and partnering with data analysts and domain teams (engineering, CX, etc.) who own their respective adoption metrics.

• Partner with Learning & Development and engineering teams to build and deliver AI training, prompt libraries, and enablement resources tailored to different roles and workflows.

• Embed with teams across the company to understand their workflows, identify where AI can accelerate their work, and just as importantly, where it shouldn't be used.

• Communicate AI strategy, risk trade-offs, and recommendations clearly to audiences ranging from junior engineers to C-level executives, including respectfully challenging perspectives when the data warrants it.

• Stay current with the rapidly evolving AI product landscape and proactively assess new capabilities (e.g., new platform features, agent frameworks) for security implications and business value.

What it takes

• 7+ years of experience in security engineering, platform engineering, infrastructure engineering, or IT engineering.

• Experience building and presenting decision frameworks, risk assessments, or strategy recommendations to senior leadership.

• Ability to operate independently, setting your own strategy, building stakeholder relationships, and executing with minimal oversight.

• Strong communication skills across a wide range of audiences, from mentoring junior engineers to partnering with executives in strategy discussions.

• Proficiency in at least one object-oriented programming language (e.g., Python, Go, Ruby, Java) with the ability to build integrations, tooling, and automations from scratch.

• Hands-on experience administering or deeply integrating with AI/LLM platforms. Not just using them, but managing them at the platform level (e.g., building MCP servers, extending LLM functionality, managing enterprise AI admin consoles).

• Experience designing scalable internal systems and infrastructure. You think about solving categories of problems at the platform level, not building one-off solutions.

• Track record of owning company-wide programs that delivered measurable impact to downstream users or the business.

• Experience with observability or SIEM tooling (e.g., Datadog, Splunk) and building data pipelines for monitoring and compliance.

Nice to have

• Understanding of LLM internals, including transformer architectures, tokenization, context window management, RAG patterns, prompt engineering techniques, and the security risks inherent to each (e.g., prompt injection, data leakage through context, output manipulation).

• Prior experience in an AI governance, AI enablement, or AI strategy role.

• Experience with observability or SIEM tooling (e.g., Datadog, Splunk) and building data pipelines for monitoring and compliance.

• Familiarity with security and compliance considerations specific to AI tooling, such as data residency, DLP policies for AI-generated content, agent access controls, and OAuth scoping for third-party integrations.

• Experience building internal enablement programs, whether training courses, documentation, or developer advocacy, that drove measurable adoption of new tools or practices.

Salary Range:

San Francisco: the pay range for this role is $204,000 - $280,500 per year.

This role will also be eligible for equity and benefits. Actual base pay will be determined based on permissible factors such as transferable skills, work experience, market demands, and primary work location. The base pay range provided is subject to change and may be modified in the future.

**Hybrid the company employees currently go into the office 3 days per week on Tuesdays, Thursdays, and a third flex day of their choosing (Monday, Wednesday, or Friday).* Additionally, hybrid in-office roles will have the flexibility to work remotely up to 4 weeks per year. Specific Workplace and Information Technology positions may require onsite attendance 5 days per week as will be indicated in the job posting.*

Why you'll love working at the company

• Move fast: You'll own meaningful problems that serve customers around the globe with the agency to move fast and see your results clearly.

• Equipped to scale: We invest in what matters, including the latest enterprise AI tools, to help you work smarter and get more out of every day.

• Best in class: Our team is full of sharp, kind, and generous colleagues who care about their craft and about helping you grow in yours.

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