- Location
- New York, New York, United States · published
- Workplace
- Hybrid
- Department
- Engineering
- Seniority
- Manager
- Source
- Workable
Description
Location
Hybrid: New York, NY (2-3 days per week in office). The office is located in Midtown West, less than a 10-minute walk from Port Authority and under 5 minutes from Penn Station and Herald Square.
SHAPE THE FUTURE OF AI GOVERNANCE WITH USERCENTRICS
Usercentrics is a global leader in consent management, and now we're bringing that same mission of trust and control into the AI era. MCP Manager (MCPM) is our newest product: a governance and management platform for Model Context Protocol (MCP), the emerging standard that connects AI agents to business systems like Salesforce, Confluence, Slack, and GitHub.
As AI adoption accelerates, enterprises face a new and urgent challenge: how do you give teams the power of AI agents while maintaining visibility, security, and control over what those agents can access and do? MCP Manager is the answer, serving as the trust and control layer for AI agent connections.
This is a category-creation opportunity. MCP is being compared to the invention of the USB connector for AI: a universal standard that changes everything. We're looking for a Software Engineer who wants to be on the ground floor of defining that category and to build the product enterprises rely on to govern their AI agents.
THE ROLE
As a Software Engineer on the MCP Manager team, you will build the features customers use to govern their AI agents, such as gateway configuration, identity and access policies, and audit logging. You will split your time evenly between our Vue.js front end and our Python/Django and TypeScript back end, all running on Google Cloud Platform. You will work closely with our Product Manager, our designer, and your fellow engineers to take features from spec to production, and you will own the quality of what you ship.
You will join a small, high-ownership engineering team that operates like a startup inside a larger company, with a short path from customer feedback to shipped code. The role exists now because buyers are moving from AI experiments to production agent rollouts, and they need the governance layer beneath those agents to keep pace with new MCP servers, clients, and security requirements.
YOUR TASKS
Feature Development
- Design, build, and ship features across the full stack, from Vue.js interfaces to Python/Django and TypeScript services.
- Turn product specs and designs into working software, raising questions and tradeoffs early with product and design.
- Design clear APIs and data models that other engineers can understand and extend.
Quality & Reliability
- Write automated tests alongside your code and help keep the test suite fast and reliable.
- Review teammates' pull requests thoughtfully and respond constructively to feedback on your own.
- Investigate and fix bugs, including issues escalated from customers, by tracing problems across the front end, back end, and infrastructure.
AI-Assisted Development
- Use Claude Code and other AI coding assistants every day to plan, write, test, and review code, while taking full ownership of everything you ship.
- Share techniques that make the team faster and help refine how we use AI tooling in our engineering practices.
Collaboration & Growth
- Contribute to planning and technical discussions with honest estimates and early warnings about risk.
- Build a working understanding of MCP and of how enterprises connect AI agents to their business systems.
- Document what you build so that teammates and future engineers can pick it up quickly.