Staff Software Engineer - Agentic AI Product

Enterprise Customer Engineering & Escalations Troubleshoot and resolve complex production issues involving distributed systems, large-scale data, and integrations. Work directly with Customer Success, Solutions Engineering, and Support teams to deliver timely, high-quality resolutions. Lead root cause analysis and drive systemic fixes to prevent recurrence. Design and build customer-facing enhancements, integrations, and custom workflows that scale across the platform. Establish best practices for observability, debugging, testing, and incident response in customer-facing systems. Own end-to-end design and implementation of complex, cross-cutting features spanning multiple services or product areas. Drive architectural decisions focused on reliability, performance, extensibility, and maintainability. Partner closely with Product Management, Platform Engineering, and Applied AI teams to deliver solutions aligned with customer outcomes. 8+ years of professional software engineering experience, including ownership of production systems at scale. Strong backend engineering experience (e.g., Java, Python, Scala, or similar) with distributed systems. Proven experience handling enterprise customer escalations and complex production issues. Deep understanding of system design, APIs, data pipelines, and service-oriented or microservices architectures. Ability to operate effectively in ambiguous environments with competing customer and platform priorities. Demonstrated experience mentoring engineers and influencing technical direction across teams. Hands-on experience building frontend applications with React, Angular, and related UI frameworks Strong communications skills. Experience in Customer Engineering, Solutions Engineering, or post-sales technical roles within a SaaS company. Familiarity with enterprise integrations, data ingestion pipelines, and customer-specific configurations. Experience working with cloud infrastructure (AWS, GCP, or Azure) and production monitoring tools. Exposure to AI/ML-enabled platforms or data-intensive products.