Design, build, test, and operate production capabilities hands-on, with documentation and evidence by default.
Leverage GenAI capabilities in your own engineering workflow — coding assistants, agent-based automation, AI-assisted testing and debugging — to accelerate delivery, including SDLC automation opportunities.
Work within the bank’s SDLC gates, security standards, and separation-of-duties model; produce the artifacts and evidence each gate requires.
Partner across governance, architecture, cybersecurity, and application teams; communicate clearly with technical and business audiences.
Pair for capability transfer — FTEs with contractor counterparts, contractors with FTE track owners — so knowledge stays when engagements end.
Participate in support rotations for live workloads with incident triage and root-cause discipline.
Skills
Must have
SE III (61 IC): Associate’s + 7 years or Bachelor’s + 5 years systems analysis/application development experience (or combined 9 years).
SE II (60 IC): Associate’s + 5 years or Bachelor’s + 3 years equivalent experience (or combined 7 years).
Strong software engineering fundamentals: architecture, API design, integration patterns, secure coding, testing, CI/CD, and operational support.
Hands-on experience with GenAI models and AI-assisted development workflows (coding assistants, prompt engineering, RAG/context engineering, or agent-based automation).
Hands-on Azure experience relevant to the target track (e.g., APIM, Entra ID, Key Vault, Azure AI services including Azure AI Foundry, Azure Monitor, IaC tooling) — current stack is Azure AI Foundry + APIM, with the platform designed to extend to additional venues and tools (e.g., AWS Bedrock, Google Vertex, direct provider APIs) without rework.
Experience delivering and operating production systems in a controlled-change environment.
Strong communication, collaboration, documentation, and stakeholder engagement skills.
Nice to have
Demonstrated depth in one or more tracks above — candidates are routed by strongest track fit across both organizations.
Financial services or other highly regulated industry experience; familiarity with audit-evidence expectations.
Experience with GitLab Duo, Azure AI Foundry, Copilot Studio, Dynatrace, Delphix, or comparable track-relevant tooling.
Certifications or demonstrated training in cloud engineering, AI engineering, DevOps, SRE, or related disciplines