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Salary
$142k – $277k per year (Estimated)
Location
In office (Plano)
Overview
Company
Impact
Profile match
JPMorganChase is the largest bank in the United States by assets and one of the most systemically important financial institutions in the world, with a lineage running back through more than a thousand predecessor firms to the 1799 founding of the Bank of the Manhattan Company. It combines a dominant investment bank and markets business with Chase, the largest retail banking franchise in America, plus commercial banking and asset and wealth management. Headquartered in New York, the group is unusual among banks for the scale of its technology spending, running one of the largest engineering organisations of any financial institution and deploying its own internal AI platform across the firm.

Be an integral part of an agile team that's constantly pushing the envelope to enhance, build, and deliver top-notch technology products.

As a Lead Software Engineer at JPMorganChase within Cloud Foundation Services, you are a hands-on technical leader on an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. You will drive business impact by owning end-to-end design and delivery of critical systems and leading engineering execution. You will apply strong technical expertise in API design and production AI application development (ADK/LangGraph) to solve complex problems across multiple technologies and applications.

Job responsibilities

  • Leads the technical design and implementation of software solutions, including system architecture, component design, and integration patterns
  • Owns hands-on delivery of production AI/agentic applications using ADK and LangGraph (mandatory)
  • Defines and implements API design standards (REST/contract-first) and partners with consumers to ensure usability and reliability
  • Writes secure, high-quality, production-ready code (Python preferred) and supports team standards through code and design reviews
  • Designs, develops, and troubleshoots with consideration of performance, resiliency, and operational readiness
  • Builds and maintains AI application quality controls and guardrails appropriate for production use

    Partners with cross-functional teams (Product, Security, SRE, and peer engineering teams) to translate requirements into well-designed APIs and reliable services

  • Drives improvements across the SDLC toolchain (CI/CD, test automation, security scanning, dependency management) to improve delivery velocity and quality

Required qualifications, capabilities, and skills

  • Expert-level proficiency in Python and strong experience building backend services in enterprise environments
  • Hands-on production experience building AI applications using ADK and LangGraph (mandatory), including operating and maintaining them in production
  • Formal training or certification on software engineering concepts and 6+ years applied experience (or equivalent experience)
  • Strong hands-on experience in system design, application development, testing, and operational stability for production services
  • Strong experience with API design and implementation using FastAPI (or equivalent), including REST service and microservice development best practices
  • Strong understanding of software design principles and patterns and ability to apply them in production systems
  • Experience with relational databases (e.g., Postgres) including strong SQL fundamentals
  • Proficient in coding in one or more languages and able to learn new technologies quickly; able to guide others in adoption and best practices
  • Experience developing, debugging, and maintaining code in a large corporate environment with modern programming languages and database querying languages
  • Solid understanding of agile methodologies and engineering practices such as CI/CD, application resiliency, performance engineering, and security-by-design
  • Ability to lead technical discussions and drive alignment across stakeholders (design reviews, trade-offs, delivery plans, and risk management)

Preferred qualifications, capabilities, and skills

  • Hands-on experience building and operating cloud-based applications on AWS environments
  • Familiarity with containers and CI/CD practices in production environments
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