• Possess ability to develop complex database queries using SQL
• Working knowledge of source code management tool and job scheduler
• Strong business analysis skills with proven experience in proposing and developing solutions
• Strong systems analysis experience
• Comfortable with maintenance of existing code base as well as new development
• Well organized with proven success in managing assignments (supporting end users) to timely completion
• AI-native engineer: Demonstrated expert-level, daily use of AI assistants (e.g., Gemini, Claude, ChatGPT, Copilot or equivalent) to accelerate delivery across the SDLC (design, implementation, testing, debugging, documentation, and operations).
• Own the outcome: Uses AI to increase speed and quality, but remains fully accountable for correctness, security, maintainability, and production readiness.
• Validation discipline: Can verify AI outputs (tests, code review rigor, threat/security checks, performance considerations) and explain why a solution is correct—not just that the tool suggested it.
• Practical workflows: Experienced applying AI to real engineering work such as: refactoring, test generation, CI/CD automation, log/trace analysis, incident triage, runbooks, and writing clear technical docs/ADRs.
• Secure and responsible use: Understands safe AI usage (no sensitive data leakage, compliant handling of customer/company information, proper IP awareness, follows enterprise guardrails).
• Force multiplier mindset: Proactively shares patterns and best practices; senior engineers are expected to coach/mentor others on effective AI-assisted engineering.