- Comfortable with Kubernetes and production systems
2. Key Technical Requirements
Core Skills
- Strong problem-solving, coding, and system design
- Java is the primary language and must be strong
- Secondary scripting exposure: Python or Bash (nice to have)
- Strong experience building backend services and APIs
- REST is required
- gRPC is a plus , not mandatory; can be learned on the job
DevOps / Cloud
- CI/CD using Jenkins
- Docker and Kubernetes experience required
- AWS familiarity preferred , but not required
Database
- Strong SQL
- Experience with Oracle
Testing
- Unit testing using JUnit, Mockito, or EasyMock
- Primary focus: Backend development (70–80% hands‑on coding and design)
- Secondary focus:
- Technical solutioning
- Code reviews (used as mentoring moments)
- Involvement in technical interviews
- Workstreams include:
- Supporting and enhancing existing production services
- Designing and building new backend services
4. Business Context
- The team builds ecosystem tooling that supports deployment and testing of AI models.
- Engineers do not build AI models .
- Focus is on enabling data science teams with reliable, scalable deployment pipelines.
- Payments or financial services background is not required .
5. Soft Skills
- Clear communication and ability to explain design decisions
- Strong team player with a mentoring mindset
- Comfortable working independently and unblocking themselves
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