Lead Software Engineer - Consumer Community Banking

Title: Lead Software Engineer, Consumer & Community Banking, Travel

As a Lead Software Engineer within Chase Travel, you will guide an agile team to design, build, and operate secure, stable, and scalable products. You will own technical outcomes end‑to‑end, set engineering standards, and mentor engineers while advancing AI‑First development practices that responsibly improve delivery speed, quality, and reliability.

What you’ll do

• Technical leadership and delivery
• Lead the design and implementation of complex services and features across upstream/downstream systems; drive architecture decisions, API contracts, and versioning.
• Own production readiness and operational excellence: SLOs, observability, incident management, and continuous improvement.
• Champion secure‑by‑default and resilient designs (timeouts, retries, circuit breakers, bulkheads) and guide the team through trade‑offs.
• Hands‑on engineering
• Write high‑quality, secure code (Java, Spring Boot, React/Next.js) and perform rigorous code reviews that reinforce standards in testing, security, and performance.
• Apply SDLC tooling to automate quality (CI/CD, code quality gates, test automation, dependency/security scanning).
• AI‑First engineering practices
• Integrate approved, privacy‑safe AI assistants into the development workflow with human‑in‑the‑loop review and objective CI gates.
• Use AI to accelerate test generation, documentation, and static analysis triage; measure impact on throughput, defect rates, and code quality.
• For AI features (if applicable), apply guardrails and evaluation: offline test sets, precision/recall metrics, latency budgets, and safe fallback paths.
• Collaboration and influence
• Coordinate with product, architecture, and partner teams to align priorities, reduce integration risk, and ensure backward compatibility.
• Mentor and coach engineers; lead design reviews and architecture decision records; foster an inclusive, high‑trust team culture.
• Required qualifications, capabilities, and skills
• 8+ years of professional software engineering experience, including 1–3 years leading delivery for a squad or stream of work.
• Proven expertise in one or more: Java, Spring Boot, React/Next.js; strong grasp of data structures, algorithms, and system design.
• Hands‑on experience with system design, application development, testing strategy, and operational stability in large, distributed environments.
• SDLC excellence: CI/CD pipelines, automated testing (unit, integration, contract, E2E), code quality gates, and observability (logs, metrics, traces).
• Security and resiliency: OWASP Top 10, OAuth2/OIDC, secrets management, encryption in transit/at rest, and resilient integration patterns.
• Database proficiency: SQL and a NoSQL store; query optimization, indexing, transactions, and caching strategies.
• Agile delivery at scale; experience guiding teams through trade‑offs and phased rollouts with feature flags and safe rollback.
• AI‑First development exposure: experience operationalizing AI assistants or AI‑powered dev workflows with governance, prompt hygiene, and measurable outcomes.

Preferred qualifications, capabilities, and skills

• Familiarity with modern front‑end frameworks and Web performance/accessibility best practices.
• Exposure to AWS (e.g., ECS/EKS/Lambda, API Gateway, RDS/DynamoDB, S3, CloudWatch, IAM) and cloud‑native resiliency patterns.
• Experience introducing evaluation frameworks for AI features or dev tooling (offline test sets, canarying models/tools, telemetry and drift detection).
• Domain experience in travel/booking or similar transactional systems.
• Formal training/certifications in software engineering, cloud, or security.

How we measure success

• Reliability and security: SLOs met, reduced incident rates/MTTR, timely remediation of vulnerabilities.
• Delivery and quality: increased deployment frequency, reduced change‑failure rate, improved test coverage and mutation score.
• Team impact: improved code review quality and cycle time; mentoring outcomes and cross‑team collaboration effectiveness.
• AI‑First outcomes: measurable improvements in developer throughput and defect detection without compromising privacy or security.
• Day‑to‑day technologies
• Backend: Java, Spring Boot; RESTful APIs; message/eventing where appropriate
• Frontend: React/Next.js
• Data: SQL and NoSQL; caching (e.g., Redis)
• Platform/DevOps: Git, CI/CD pipelines, containerization, observability stack
• Security: SAST/DAST, dependency scanning, secrets management
• AI‑assisted dev: governed coding assistants, test generation, static analysis triage with human review and CI gates
• Inclusive culture We value diverse perspectives and a culture of inclusion, mentorship, and respect. You help create a collaborative environment where engineers grow and deliver their best work.