- Demonstrated experience using approved AI-assisted engineering tools and
practices across the software development lifecycle, with an understanding of validation, secure coding, peer review, automated testing, and responsible adoption at scale.
- Demonstrated experience leading effective use of enterprise-authorized
AI-assisted software development tools within the work environment (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security
- Strong understanding of responsible AI use in engineering workflows,
including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching senior engineers/leads on compliant usage patterns and controls.
- Deep expertise in Java 8+ / Spring Boot, microservices, and React/Angular.
- Strong Kafka/event-driven architecture experience (retries, idempotency, DLQ
patterns, schema/versioning).
- Experience with SQL databases with data modelling, query optimization and
performance tuning.
- Strong NoSQL experience: Cassandra / DynamoDB / Elastic Search (data
modeling, reliability, scale).
- Strong experience with Cloud Foundry/AWS and CI/CD strategy and execution.
- Ability to work with tools such as Dynatrace, Splunk, Grafana for