About the role
About Workato Workato delivers enterprise infrastructure for the agentic era, redefining iPaaS and helping enterprises unify data, applications, processes, and AI into a single, governed platform. A leader in Enterprise MCP and trusted by 50% of the Fortune 500, Workato’s cloud-native architecture connects every application, data source, and process to power real-time orchestration at scale. With enterprise-grade security and continuous innovation at its core, Workato provides the trusted foundation for organizations to automate with confidence and operationalize AI across the business. To learn more, visit www.workato.com
Why join us? Ultimately, Workato believes in fostering a flexible, trust-oriented culture that empowers everyone to take full ownership of their roles . We are driven by innovation and looking for team players who want to actively build our company. But, we also believe in balancing productivity with self-care . That’s why we offer all of our employees a vibrant and dynamic work environment along with a multitude of
benefits they can enjoy inside and outside of their work lives. If this sounds right up your alley, please submit an application. We look forward to getting to know you! Also, feel free to check out why: Business Insider named us an “enterprise startup to bet your career on” Forbes’ Cloud 100 recognized us as one of the top 100 private cloud companies in the world Deloitte Tech Fast 500 ranked us as the 17th fastest growing tech company in the Bay Area, and 96th in North America Quartz ranked us the #1 best company for remote workers This role requires working during USA working hours (8:00 pm - 5:00 am IST)
Responsibilities We are hiring a Customer Centric Engineer to join our Global Customer Centric Engineering team and help deliver Customer satisfaction by solving the toughest technical customer escalations fast and championing a trust strategy throughout the company. The Customer Engineering team sits at the intersection of Product Engineering and our Success and Support organization, acting as the deepest technical escalation layer for our most critical customer issues. As a Customer Centric Engineer on this team, you will own the end-to-end lifecycle of complex technical escalations — from root cause analysis through code-level fixes — while also driving long-term improvements to how Workato is built, debugged, and supported at scale. This role requires both the depth of a engineer and the communication range to work fluidly across engineering, support, and customer-facing teams. You will also play a key role in how we adopt AI across our support workflows, tooling, and troubleshooting processes — finding practical ways to apply emerging capabilities to real operational problems. In this role, y ou will also be responsible to: Own complex technical escalations from our Success and Support teams, applying programming, database, API, and UI expertise to resolve critical customer issues end-to-end. Identify root causes using systematic troubleshooting techniques and full access to R&D tooling, systems, and codebases. Leverage AI tools and techniques — including LLM-assisted log analysis, code search, and pattern recognition — to accelerate root cause identification and reduce mean time to resolution. Dig into source code to propose test cases, reproduce defects, and deliver or recommend fixes to Product Engineering. Build and maintain internal diagnostic tools and utilities — including AI-assisted tooling — that improve support efficiency and reduce time-to-resolution across Workato teams. Communicate root cause analyses, workarounds, and resolution timelines to customer-facing teams within defined SLA windows to drive customer satisfaction. Mentor Support engineers on technical concepts, debugging approaches, and best practices. Author and maintain internal knowledge base documentation to reduce repeat escalations and build team capability. Build trusted relationships across Success, Product Engineering, and Infrastructure as a recognized technical expert. Champion supportability and debuggability initiatives within Product Engineering, ensuring new features are built with observability and diagnosability in mind. Identify and drive AI-powered process improvements across the escalation lifecycle — from triage and classification to documentation generation and knowledge base maintenance.
