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Sr. Lead Software Engineer at JPMorgan Chase, Columbus, OH

Sr. Lead Software Engineer at JPMorgan Chase in Columbus, OH. Est. up to $200k. Apply with swipeandhired.

If you are excited about shaping the future of technology and driving significant business impact in financial services, we are looking for people just like you. Join our team and help us develop game-changing, high-quality solutions.

As a Senior Lead Software Engineer at JPMorgan Chase within Consumer and Community Banking, you will be a key member of a team designing and delivering high-quality architecture solutions across software applications and platform products. You will drive business impact by applying deep technical expertise and structured problem-solving to challenges spanning multiple technologies. You will shape future-state and target-state architecture and influence strategic technology decisions that enable growth, operational excellence, resiliency, and innovation across the firm.

Job responsibilities

Provide technical leadership and direction to product and engineering teams to deliver outcomes aligned to business priorities.

Own end-to-end solution and product architecture for key initiatives, including target-state designs, integration patterns, APIs, and data flows aligned to enterprise standards.

Drive architectural decisions and trade-offs across security, resiliency, performance, cost, and time-to-market; manage dependencies and technical risk.

Translate product capabilities into scalable system designs, APIs, and data models with clear non-functional requirements .

Establish and govern reference architectures, design patterns, and reusable components to accelerate delivery, consistency, and reuse across teams.

Partner with product management to shape the roadmap, influence product design, and prioritize architectural investments and technical debt reduction.

Guide solution design and implementation across teams, conducting design and code reviews as needed to ensure architectural consistency, quality, and maintainability.

Drive adoption and governance of approved AI-assisted engineering practices to improve code quality, delivery speed, and operational outcomes (e.g., code review/refactoring, test acceleration, release readiness, incident/root-cause analysis), including measurable validation standards and SDLC/TLM automation.

Apply deep SDLC/toolchain knowledge (CI/CD, testing, automation, observability, and approved AI-assisted capabilities) to increase value realized from automation at scale.

Serve as a function-wide subject matter expert in one or more focus areas and contribute to the engineering community by advocating firmwide frameworks, tools, and SDLC practices.

Required qualifications, capabilities, and skills

Formal training or certification on software engineering concepts and 5+ years applied experience

Strong experience owning solution/platform architecture and system design for distributed systems, including trade-offs across security, resiliency, performance, cost, and time-to-market, and driving decisions through architecture reviews/governance.

Proven background designing and delivering microservices, APIs, and event-driven architectures (e.g., Kafka), including integration patterns and service boundaries.

Hands-on cloud-native engineering experience across multi-cloud and hybrid environments, with strong AWS expertise.

Track record of building reusable capabilities (APIs, services, frameworks, reference architectures) and scaling adoption across lines of business via standardization and self-service enablement.

Strong partnership skills with Tech Partners and Engineering Leads to review designs, evaluate alternatives, set architectural guardrails, and eliminate anti-patterns by promoting approved patterns and spec-driven development.

Experience with Java, Python, and React (or comparable technologies), including the ability to review code, assess implementation approaches, and support engineering teams in delivering secure, scalable, and high-quality solutions.

Experience using firm-approved AI-assisted engineering tools (coding, code review, test acceleration, troubleshooting), including practices to validate AI outputs for correctness, performance, and security, and to apply responsible AI controls (data sensitivity, secure handling, resiliency/security expectations).

Strong judgment, communication, and stakeholder management skills, with the ability to influence technical direction across multiple teams and senior technology stakeholders.

Ability to evaluate current and emerging technologies and recommend best-fit approaches for future-state architecture.

Preferred qualifications, capabilities, and skills

Experience building and leveraging AI agents and reusable skills/components in production environments.

Banking/Financial Services domain expertise, including familiarity with the regulatory and controls environment.

Experience operating within formal architecture governance frameworks (e.g., TOGAF or equivalent).

Experience driving large-scale platformization efforts (shared services, standardization, self-service adoption, reusable reference architectures).

Deep expertise with platform/runtime components such as caching (Redis, Memcached) and workflow/orchestration (Airflow, Temporal).

AWS Certified Solutions Architect (Associate or Professional) certification preferred.