Principal Software Engineer - Platform Engineering Workflow Automation

About the team We build the workflow and automation engines that power how work gets done across the ServiceNow Platform. Our engines process billions of workflow transactions every month across enterprise customers, and we're now extending that foundation to support AI-native, agentic workflows. This is a team that cares about getting the architecture right, not just shipping features. We spend real time on performance, reliability, and making sure the platform holds up as customers push more volume and more complexity through it. What you'll do As a Principal Software Engineer, you'll take on hard architecture problems across our workflow and automation stack, including how we evolve it toward agentic, AI-driven execution at scale. Lead architecture and technical direction for problem areas across the portfolio, working with product and engineering leads to figure out what's blocking progress and where the real opportunities are. Get hands-on. Build the prototypes and reference implementations that prove out an architectural idea before a whole team commits to it. Test ideas with real experiments and real data, not just design docs. Use what you learn to shape the direction. Help move existing workflow capabilities toward AI-native patterns: agentic execution, better use of context and data, more autonomous flows, and connect that to concrete engineering work. Dig into cases where an agentic feature exists but isn't delivering the value it should. Figure out if it's the architecture, the data, the UX, or the cost model, and drive the fix. Write down the patterns and tradeoffs that work so other teams don't have to rediscover them. Sit in on design reviews and tough calls across teams. Push back with data when something looks risky, and help teams weigh shipping speed against long-term durability. Work across engineering teams to share what's working and help good patterns spread faster. What we're looking for 15+ years of engineering experience, or equivalent. Real experience building and running large-scale distributed systems: workflow engines, integration platforms, data-heavy products, or cloud infrastructure. Solid grasp of system design for scale, reliability, observability, and production readiness, including database architecture at high transaction volume. Strong depth in Java, Python, or a comparable language. A track record of setting technical direction and influencing architecture across teams, even without a formal reporting line. Comfortable leading through credibility and collaboration rather than title. Good judgment on when to invest in long-term architecture versus when to just ship. Experience mentoring senior engineers and building patterns that other teams actually reuse. Experience with AI-powered products, agentic systems, or workflow automation platforms is a strong plus. Comfortable reasoning about AI-assisted workflows: data quality, correctness, evaluation, safety, and where a human needs to stay in the loop. Bonus if you've worked on large-scale enterprise customers or led complex platform migrations. Why this role You'd be shaping how our workflow and automation engines move into an agentic future, on a platform that already runs at serious scale. You'd work with teams that care about doing this well, not just doing it fast. To be successful in this role, you have: 15+ years of related engineering experience, or equivalent practical experience. Strong experience building and operating large-scale distributed systems, workflow engines, integration frameworks, or cloud-scale infrastructure handling high transaction volume. Deep understanding of system design for scale, reliability, observability, fault tolerance, data quality, security, and production readiness. Strong technical depth in Java, Python, or similar programming languages. Proven ability to define technical direction, influence architecture across teams, and translate ambiguous product strategy into executable engineering plans. Abilit