About the company
ServiceNow is the AI control tower for business reinvention. Our ServiceNow AI platform brings together any AI, any data, and any workflow— helping 85% of the Fortune 500® work smarter, faster, and better.
Responsibilities
- Lead architecture and technical direction for problem areas across the portfolio
- 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
- Help move existing workflow capabilities toward AI-native patterns: agentic execution, better use of context and data, more autonomous flows
- 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
- Work across engineering teams to share what's working and help good patterns spread faster
Requirements
- 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
- 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