Sr Quality Assurance Engineer (Customer Facing)

Workday•San Francisco, CA

6d•$117,800 - $218,400•Hybrid

About The Position

The Pipedream team enables AI agents to connect to the software and services people use every day — including Notion, GSuite, Slack, Zoom, GitHub, Jira, and thousands more. Our platform is used by software developers at leading technology companies like Workday, Perplexity, Meta, and Relevance AI who are building AI agents and workflow products. Pipedream offers something rare: the opportunity to work in a startup environment while delivering enterprise-scale impact. Acquired by Workday in December 2025, we are a team where you can move fast, wear multiple hats, and see your work directly shape a product's direction. If you are energized by working at the intersection of developer tools and AI, and you want to make a meaningful impact on how the next generation of intelligent software gets built, this is the team for you. As a Sr. Quality Assurance Engineer on the Pipedream team, you will serve as a player/coach who is hands-on with the most complex problems while also elevating the capabilities of the team around you. This is a customer-facing role: you will work directly with software developers and partner teams using Pipedream in production, helping them debug issues, improve reliability, and shape how the platform evolves based on real-world feedback. This is not a people management role — you will be the person the team looks to when escalations come in, when a partner issue requires careful navigation, or when someone needs a thought partner on a difficult challenge. You will work closely with both internal teams at Workday and external customers who are building products on top of Pipedream.

Requirements

7+ years of related work experience in QA, solutions or support engineering, forward deployed engineering, or a closely related function working with technically sophisticated software developers
Strong hands-on technical skills, with the ability to develop in JavaScript or Python and reason about production code
Proficiency working with APIs, troubleshooting API request failures, and using API documentation
Excellent customer service and communication skills, with the ability to credibly engage both software developers and non-technical users in a customer-facing capacity
Working knowledge of AI concepts including LLMs, agents, tool calling, evals, and MCP
Bachelor’s degree in Computer Science, Engineering, or a related field (or equivalent practical experience)

Nice To Haves

Passion for AI products, with hands-on experience using AI coding tools (e.g., Claude Code, Codex, Cursor) and building AI agents or agentic workflows
Experience supporting platforms with large, complex surface areas and managing competing priorities in a customer-facing environment
Experience mentoring or leading other team members
Strong analytical thinking, with the ability to break down complex technical problems into their fundamental parts, identify patterns across support issues, and use logical reasoning to drive root cause analysis and inform process improvements
A detail-oriented mindset, with the ability to spot errors or inconsistencies that others may overlook, manage complex information across multiple issues and accounts, and maintain a high level of accuracy and consistency in your work
Strong collaboration and interpersonal skills, with the ability to work effectively across product, engineering, and support teams, leverage diverse perspectives to solve problems, and foster a culture of mutual respect and shared learning
A genuine passion for learning and intellectual curiosity — you enjoy picking up new technologies and diving into unfamiliar problem spaces
Comfortable working asynchronously across multiple time zones on a geographically distributed team

Responsibilities

Supporting software developers across the full range of issues, from troubleshooting technical errors (including authentication failures, malformed requests, and rate limits) to billing, feature requests, and general account questions
Owning the most complex integration issues and sensitive partner escalations, reviewing how teammates approach difficult problems, pairing on debugging, and helping the team grow into more confident operators
Identifying technical and usability issues with connectors and collaborating with product and engineering to prioritize and resolve them
Driving continuous improvement of support and quality processes, including playbooks, internal tooling, documentation, and automations to help the team scale