Design, develop, and maintain secure, high-quality production code and platform services for an AI/ML and data platform. Provide Databricks and AWS platform administration and engineering support, optimize infrastructure and CI/CD, apply SRE principles, automate remediation, and collaborate with data science, engineering, and vendors while guiding responsible AI-assisted development practices.
We have an exciting and rewarding opportunity for you to take your software engineering career to the next level.
As a Software Engineer III at JPMorganChase within the AI/ML and Data Platform, 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.
Job responsibilities
- Executes software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems.
- Creates secure and high-quality production code and maintains algorithms that run synchronously with appropriate systems.
- Performs platform design, set-up and configuration, providing engineering support to data engineering teams, Data Science/ML, and Application/integration teams.
- Collaborates with engineering and data teams to optimize infrastructure and deployment processes, focusing on automation and operational excellence.
- Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems.
- Leverages enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity across complex deliverables (e.g., code generation/refactoring, unit test creation, documentation), while validating outputs through peer review, automated testing, and secure coding standards; contributes learnings and reusable patterns to improve broader team effectiveness.
- 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.
- Leads evaluation sessions with external vendors, startups, and internal teams to drive outcomes-oriented probing of architectural designs, technical credentials, and applicability for use within existing systems and information architecture.
- Contributes to software engineering communities of practice and events that explore new and emerging technologies
- Adds to team culture of diversity, opportunity, inclusion, and respect
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and applied experience.
- Extensive experience with AWS Databricks platform administration and engineering support is a MUST.
- Strong understanding of SRE principles, including SLIs, SLOs, error budgets, and incident management.
- Experience with monitoring tools, automation frameworks, and CI/CD pipelines.
- 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.
- Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; ability to guide peers on safe and effective usage within team practices.
- Proficient in Python and/or Java application program development with use of automated unit testing.
- Solid understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
- Knowledge of Big Data distributed compute frameworks like Spark, Glue, MapReduce etc.
- Excellent troubleshooting, analytical, and communication skills.
Preferred qualifications, capabilities, and skills
- Experience in Data pipelines using Spark
- Exposure to AWS & Databricks Platform administration.
- Knowledge of containerization (Docker, Kubernetes) and orchestration.
- Familiarity with distributed systems and large-scale data processing.
We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.
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Top Skills:
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