If you are a software engineering leader ready to take the reins and drive impact, we’ve got an opportunity just for you.
As a Director of Software Engineering at JPMorganChase within Consumer & Community Banking, you lead a technical area and drive impact within teams, technologies, and projects across departments. Utilize your in-depth knowledge of software, applications, technical processes, and product management to drive multiple complex projects and initiatives, while serving as a primary decision maker for your teams and be a driver of innovation and solution delivery.
Job responsibilities
- Leads technology and process implementations to achieve functional technology objectives
- Directly manages multiple areas with strategic transactional focus
- Manages multiple stakeholders, complex projects, and large cross-product collaborations
- Sets direction and governance for agentic AI-enabled engineering and SDLC/TLM automation within a technical area to drive measurable improvements in speed, quality, and operational outcomes (e.g., AI-orchestrated delivery workflows, release readiness controls, automated test modernization, and incident triage acceleration), while establishing guardrails for validation, security, resiliency, traceability, and reuse across teams.
- Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation and support capacity unlock initiatives at scale.
- Makes decisions that influence teams’ resources, budget, tactical operations, and the execution and implementation of processes and procedures
- Carries governance accountability for coding decisions, control obligations, and measures of success such as cost of ownership, maintainability, and portfolio operations
- Delivers technical solutions that can be leveraged across multiple businesses and domains
- Influences peer leaders and senior stakeholders across the business, product, and technology teams
- Champions the firm’s culture of diversity, opportunity, inclusion, and respect
Required qualifications, capabilities, and skills
- Formal training or certification on data management concepts and 10+ years applied experience. In addition, 5+ years of experience leading technologists to manage, anticipate and solve complex technical items within your domain of expertise.
- Proven experience in designing and developing large scale data pipelines for batch & stream processing
- Strong understanding of Data Validation / Data Quality
- Strong understanding of Data Warehousing, Data Lake, ETL processes and experience in Big Data technologies (e.g Hadoop, Snowflake, Databricks, Apache Spark, PySpark, Airflow, Apache Kafka, Java, Open File & Table Formats, GIT, CI/CD pipelines etc. )
- Expertise with public cloud platforms (e.g., AWS, Azure, GCP) and modern data processing & engineering tools
- Excellent communication, presentation, and interpersonal skills Experience developing or leading large or cross-functional teams of technologists
- Strong understanding of responsible AI use and control expectations in engineering workflows, including data sensitivity, resiliency/security implications, and governance; ability to influence leaders on safe scaling patterns and reuse.
- Experience leading adoption of agentic AI-enabled engineering practices (using enterprise-authorized tools within the work environment) across teams, including defining operating expectations (human-in-the-loop validation, quality gates), measuring outcomes, and ensuring secure handling of sensitive inputs/outputs.
- Exhibit strong proficiency in Java or Python, with the ability to architect and build complex AI models from scratch. Ensure the delivery of secure, high-quality production code.
- Extensive practical cloud native experience
- Experience working at code level and ability to be hands-on performing PoCs, code reviews
Preferred qualifications, capabilities, and skills
- Experience in Data Modeling (ability to design Conceptual, Logical and Physical Models, ERDs and proficiency in data modeling software like ERwin)
- Experience with Data Governance, Data Privacy & Subject Rights, Data Quality & Data Security practices
- Experience in Data visualization & BI tools is a huge plus