VP, Lead Software Engineer (Backend/AWS + React | AI-first Tooling & Automation)
Role summary
We're seeking a VP-level Lead Software Engineer with a strong backend engineering profile to lead the design and delivery of scalable, secure, cloud-native services on AWS, paired with React UI experience to ensure seamless end-to-end execution within a regulated financial services environment. You'll raise the bar on reliability and operational excellence, and drive an AI-first engineering paradigm—embedding AI tooling and automation into daily development while maintaining strict adherence to regulatory, compliance, and risk management standards.
What you'll do
1. AI-first SDLC: standardize AI-assisted workflows for coding, test creation, code review, documentation, debugging, and incident response—ensuring all AI tooling usage complies with firm-wide governance, model risk management, and data privacy policies.
2. Lead backend architecture and delivery owning core services on AWS and partnering closely on React UI implementation.
3. Own technical strategy: define target backend/cloud architecture, engineering standards, and near-/long-term roadmaps aligned with business objectives, regulatory requirements, and risk appetite.
4. Design and build scalable backend systems on AWS (APIs, event-driven services, data integration, identity/security patterns, performance and cost controls) that meet financial industry standards for data integrity, auditability, and resilience.
5. Ensure strong React implementation: contribute to UI architecture where needed, guide reusable patterns, and ensure the front end cleanly integrates with backend contracts.
6. Automate engineering hygiene: CI/CD improvements, quality gates, dependency management, and developer self-service to reduce toil and increase throughput while maintaining audit trails and change management controls.
7. Drive production excellence: observability, resiliency, SLOs, incident management, and post-incident learning with measurable improvements aligned to business continuity and disaster recovery (BC/DR) standards.
8. Collaborate with risk, compliance, and information security teams to ensure all engineering practices meet regulatory expectations (., SOX, GDPR, SEC/FINRA, OCC guidelines).
9. Mentor and grow engineers: coach technical depth (especially backend/AWS), strengthen ownership, and develop future tech leads within a financial services context.
10. Stay hands-on in critical backend components and high-impact design decisions, especially where scale, security, data sensitivity, or regulatory compliance are at stake.
What success looks like (first 3–6 months)
11. Roll out AI-first engineering workflows that measurably improve developer velocity and code quality, with appropriate governance guardrails for AI usage in a regulated environment.
12. Improve delivery throughput by clarifying backend priorities, reducing blockers, and introducing measurable execution metrics—while maintaining compliance with change management and release governance.
13. Reinforce or modernize AWS backend architecture with secure, scalable defaults and clear service/API standards that satisfy internal audit and regulatory review.
14. Improve production readiness: stronger monitoring/logging/alerting and faster recovery through better runbooks and automation, aligned to firm-wide SLA and BC/DR expectations.
Required qualifications
15. Proven experience leading delivery of production backend systems (as lead engineer / tech lead / engineering lead) in financial services, preferably within an investment bank or capital markets environment.
16. Strong expertise in AWS (cloud-native architecture, security, scalability, reliability, and cost awareness) within a regulated industry context.
17. Strong backend fundamentals: API design, distributed systems concepts, data modeling, integration patterns—with experience handling high-volume, low-latency, and mission-critical financial workloads.
18. Solid React experience sufficient to guide UI architecture and ensure high-quality integration with backend services.
19. Deep understanding of financial services technology landscape: familiarity with trading systems, risk platforms, client onboarding, regulatory reporting, or similar banking domains.
20. Demonstrated ability to set technical direction across engineers and influence stakeholders, including technology risk, compliance, and business partners.
21. Strong engineering craft: testing strategy, CI/CD, observability, and operational excellence within a controlled, auditable environment.
Preferred qualifications
22. Demonstrated AI tooling adoption (coding assistants, LLM-enabled workflows) with measurable impact on quality/velocity, ideally within a governance-conscious environment.
23. Investment banking or markets technology experience (., front-office tools, middle/back-office platforms, trade lifecycle, market data, or client-facing portals).
24. Track record of building automation for developer productivity (pipelines, templates, self-service, guardrails) in a large-scale enterprise or financial institution.
25. Familiarity with event-driven architectures and asynchronous patterns on AWS, particularly for real-time financial data processing or transaction workflows.
26. Experience modernizing legacy systems incrementally within complex, regulated environments (migration strategies, strangler patterns, dual-running).
27. Strong security mindset (threat modeling, least privilege, secrets management, encryption at rest/in transit for sensitive financial data).