We are building a cloud-native platform with AI as the baseline. AI is not a feature layer. It defines how systems are designed, how data is structured, and how engineers think before building. AI in the product starts from system design and data modeling.

Engineers here are builders who own end-to-end delivery. You think about data schema, scale, and distributed systems before using AI tools. You own what you build including development, testing, release, and production operations.

• University degree in computer science, mathematics, IT or relevant professional experience with qualified technical training
• 12+ years of relevant experience
  - Strong fundamentals in distributed systems and cloud-native architecture
  - Experience building and operating production services
  - Understanding of scalability, reliability, and security
  - Experience with automation, CI/CD, and service ownership
  - Ability to use AI tools effectively while applying engineering judgment
• Working under minimal supervision

• Define technical direction for large-scale, cross-product cloud architecture
• Lead architectural decisions across:
  1. distributed systems design
  2. data architecture for AI-first products
  3. platform scalability, reliability, and security
• Evaluate trade-offs across performance, cost, customer impact, and operational risk
• Drive engineering standards, patterns, and long-term architecture evolution
• Resolve high-impact technical challenges spanning multiple teams or domains
• Guide and mentor principal engineers and architects
• Influence product direction by shaping how AI capabilities are built into the platform
• Sponsor and drive initiatives for:
  1. platform reliability at scale
  2. observability and automation maturity
  3. engineering productivity improvements
• Act as final escalation point for critical system design and production issues
• Takes responsibility proactively