Senior Staff AI Enablement Engineer Full Time NEW

About the role

SoFi is scaling how employees and AI agents safely reach the tools they need to do their jobs. We run a centralized MCP (Model Context Protocol) gateway that lets approved AI clients (Claude, Cursor, Windsurf, internal agents) connect to enterprise systems such as Slack, Google Workspace, Jira/Confluence, GitLab, Datadog, Snowflake, Glean, and ServiceNow, with SSO/OAuth brokering, policy enforcement, and full auditability.

As our Sr. Staff AI Enablement Engineer, you'll own the strategy and day-to-day operation of this platform and the customer-facing interfaces employees use to get AI tool access. You'll turn a security-approved control plane into a fast, self-service path to AI productivity across the company. You'll partner closely with Product Security, IAM, Engineering, and business leaders.

What you'll do

• Own the MCP gateway platform end to end. This covers the catalog and registry of approved MCP servers, onboarding of new connectors, OAuth scope configuration, tool-level enablement and disablement, and lifecycle and hygiene.
• Design the customer experience for AI tool access. Build intake, request, and provisioning flows (Compass/ServiceNow, Slack, Okta), documentation, and self-service paths that cut time-to-access from weeks to hours.
• Partner with Product Security and IAM on MCP approval, threat modeling, least-privilege scopes, and incident response. Turn security requirements into operational guardrails that don't block adoption.
• Run operations for the platform. This includes L1/L2 support models, runbooks, SLAs, monitoring and observability of tool usage, and vendor management (e.g., Cequence and SaaS connector vendors).
• Drive adoption and measure impact. Define and report adoption, usage, and value metrics by function to IT and SLG leadership, and identify the next high-leverage integrations.
• Automate access governance. Integrate the gateway with joiner/mover/leaver processes, access reviews, and audit evidence for SOX and regulatory requirements.
• Set technical direction. Evaluate emerging agent and tool-access standards (MCP, A2A, agent identity), build vs. buy, and the roadmap for internal and customer-facing AI interfaces.
• Mentor and influence. Guide IC1–IC4 engineers and analysts, and influence function-level decisions with senior ICs and SLG.

What you'll need 

• Education & Minimum Experience Requirements: Bachelor’s Degree + 4+ Years of Experience OR Master’s Degree + 3+ Years of Experience in software engineering or a related field.
• Track record of owning complex, companywide programs or platforms and independently handling their planning, execution, and resourcing.
• Hands-on experience with LLM and agent tooling: MCP servers and clients, API gateways, and AI coding assistants such as Claude Code, Cursor, or Copilot.
• Deep knowledge of identity and access: SSO/SAML, OAuth 2.0/OIDC, SCIM, Okta, and least-privilege and RBAC design.
• Strong integration and automation skills. That means REST/GraphQL APIs, scripting (Python, TypeScript, or similar), iPaaS (Workato or similar), and ServiceNow workflows.
• Experience operating in a regulated environment (financial services preferred), including audit, data retention, and change management.
• Ability to translate between security, engineering, and business stakeholders, and to influence without authority.

Nice to have

• Experience building or running an AI gateway, API gateway, or developer platform (e.g., Cequence, Kong, Apigee).
• Experience building Slack bots, deflection bots, or agentic workflows for IT or employee support.
• Familiarity with AI governance frameworks (NIST AI RMF) and LLM security risks (OWASP LLM Top 10, prompt injection, tool poisoning).