We have an exciting and rewarding opportunity for you to take your software engineering career to the next level.
As a Sr. Lead Software Engineer at JPMorgan Chase within the Commercial & Investment Bank's Sales & Research Technology team, you serve as a seasoned member of an agile team to design and deliver trusted market-leading technology products in a secure, stable, and scalable way. You are responsible for carrying out critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives. You are responsible for designing, building, and modernizing database-driven platforms and distributed data solutions. Focus on solution architecture, legacy modernization, cloud migration, and reliable data platforms that support investment banking, capital markets, loan systems, risk, analytics, and regulatory workflows.
Job responsibilities
- Design, build, and operate database engineering solutions across relational, distributed, and cloud-based data platforms
- Partner with technology and business stakeholders to align technical delivery with business priorities and corporate ROI
- Provide technical direction across global squads and help coordinate delivery across multiple teams and workstreams
- Drives adoption and governance of approved AI-assisted engineering practices across teams to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test acceleration, release readiness, incident/root-cause analysis), while establishing measurable validation standards (secure coding, peer review, automated testing) and promoting reuse of proven patterns and automation within the SDLC/TLM toolchain.
- Applies knowledge of tools within the Software Development Life Cycle toolchain, including approved AI-assisted development and automation capabilities, to improve the value realized by automation at scale
- Integrate database platforms with enterprise applications, data sources, analytics platforms, and AI-enabled services
- Contribute to architecture review boards, engineering standards, governance practices, and regulatory compliance processes
- Executes software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or breakdown technical problems
- Produces architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and** **5+ years applied experience
- Strong experience in database engineering, database architecture, and data platform modernization
- Proficiency in database querying languages and experience with large-scale data systems
- Experience delivering technology solutions across cloud and data platforms such as AWS, Azure, Snowflake, Databricks, Spark, or Hadoop
- Demonstrated experience leading effective use of enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security
- Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching senior engineers/leads on compliant usage patterns and controls
- Solid understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
- Demonstrated knowledge of software applications and technical processes within a technical discipline such as data engineering, cloud, distributed systems, or database platforms
- Experience working within financial services domains such as investment banking, capital markets, loan systems, risk, analytics, or regulatory compliance
Preferred qualifications, capabilities, and skills
- Familiarity with AI and data platform concepts such as LLM architecture, RAG, LangChain, or LangGraph
- Experience participating in architecture review boards, engineering governance, or capability-building initiatives
- Exposure to regulatory, risk, or control requirements in a financial services environment
- Exposure to cloud technologies