Senior Lead Software Engineer - Python, PySpark, Big Data, Data pipeline, ML/AI

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 Senior Lead Software Engineer at JPMorgan Chase within the Consumer and Community Banking - Risk Technology Portfolio team, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. Drive significant business impact through your capabilities and contributions, and apply deep technical expertise and problem-solving methodologies to tackle a diverse array of challenges that span multiple technologies and applications.

Job responsibilities:

- Executes software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or breakdown technical problems
- 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 enterprise-authorized AI-assisted development and automation capabilities, to drive efficiency and support capacity unlock initiatives across teams, prioritizing reuse of existing firm technology assets.
- Creates secure and high-quality production code and maintains algorithms that run synchronously with appropriate systems
- Drive the AI / ML delivery best practices along with software engineering best practices.
- 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.
- Define architecture for series of complex deliverables.
- Gathers, analyzes, synthesizes, and develops visualizations and reporting from large, diverse data sets in service of continuous improvement of software applications and systems
- Proactively identifies hidden problems and patterns in data and uses these insights to drive improvements to coding hygiene and system architecture

Required qualifications, capabilities, and skills:

- Formal training and certification on software engineering concepts and 5+ years applied experience. In addition, 2+ years of experience leading technologists to manage and solve complex technical items within your domain of expertise
- Hands-on practical experience in system design, application development, testing, and operational stability
- Experience in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages and database querying languages
- Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, test creation, troubleshooting, or documentation) with demonstrated ability to critically evaluate, validate, and refine AI-generated outputs for correctness, performance, and security.
- Solid understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
- Good knowledge of Machine Learning modelling as an engineer
- Experience in working with one or more programming language(s) and framework(s) (i.e., Python, PySpark, Big Data, Data pipeline, Machine Learning, etc.)
- Strong SQL skills with ability to validate features and data quality at scale
- Experience configuring and optimizing Spark clusters for processing large data.
- Hands-on experience working with AWS services including EMR, EC2, S3, and CloudWatch
- Working knowledge on Databricks in creating Data Pipelines, Machine learning models deployment.

Preferred qualifications, skills, and capabilities:

- Expertise with programming languages like Java, python
- Experience in Cloud Technologies (i.e., AWS - Databricks preferred)
- Experience with serving high volume, High availability & ultra low latency API solutions with Java - Spring Boot applications
- Awareness with Python Machine Learning libraries and ecosystems (i.e., Pandas, Numpy, etc.)
- AWS certifications (e.g. Solutions Architect Associate)
- Exposure to workflow orchestration tools (e.g. Apache Airflow)
- Familiarity with modern LLM techniques