Sr Lead Software Engineer — Python/ AWS/Databricks

Overview

In this role you drive secure, scalable software delivery for a Credit data pond within Wholesale credit risk technology. You will provide technical guidance across teams, develop high-quality production code, and advance AI-assisted engineering practices to raise code quality and delivery speed. You’ll shape the enterprise toolchain and governance to ensure secure, auditable automation at scale, collaborating with cross-functional partners. This position offers impact through solving diverse, high-stakes engineering challenges and contributing to firm-wide standards.

Responsibilities

• Provide technical guidance to business, technical teams, contractors, and vendors
• Develop secure, high-quality production code and review others’ code
• Lead adoption and governance of AI-assisted engineering practices across teams with measurable validation standards
• Establish an enterprise-aligned operating model for AI-assisted development with guardrails and auditability
• Define and enforce CI/CD quality gates and validation standards for AI-assisted changes
• Apply SDLC toolchain knowledge to enhance automation at scale
• Set enterprise toolchain strategy spanning planning, source control, build, test, security, deployment, and observability
• Establish automation-at-scale governance (golden pipelines, shared libraries, templates, guardrails)
• Influence product design, application functionality, and technical operations
• Act as a function-wide expert in one or more focus areas
• Contribute to engineering community by promoting firmwide frameworks and practices

Key requirements

• Formal training or certification in software engineering concepts
• Hands-on experience delivering system design, application development, testing, and operational stability
• Advanced in one or more programming languages
• Experience establishing scalable operating models for enterprise AI-assisted development
• Set validation expectations for AI outputs before merge/release (peer review, secure coding, automated tests)
• Experience leading enterprise-authorized AI-assisted software development tools
• Strong understanding of responsible AI use in engineering workflows and coaching others
• Establishes responsible AI governance for engineering workflows with auditability
• Defines secure handling standards for AI inputs/outputs (redaction, least privilege, logging)
• Ability to work independently with minimal oversight
• Practical cloud-native experience

• leadership
• problem-solving
• communication
• Python
• AI-assisted development tools
• CI/CD quality gates

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