Software Engineer III - AI/ML Developer

JP Morgan Chase; Plano (TX); On-site; USD 120,000 - 160,000; Full time

Job summary

JPMorganChase in Plano, TX seeks an experienced Software Engineer III to join an agile team delivering secure, scalable software components for consumer and community banking. You will design, develop, and troubleshoot production code while advancing AI-assisted practices across the SDLC.

Focus areas include ML model tooling, cloud-based ML platforms, data processing, and robust testing. The role emphasizes responsible AI, security, and collaboration across vendors and internal teams.

Qualifications

• Formal training or certification in software engineering concepts and 3+ years applied experience.
• Hands-on experience delivering system design, application development, testing, and operational stability.
• Hands-on experience building, deploying, and maintaining machine learning platforms or infrastructure.
• Proficiency in Python and ML frameworks; experience with Spark, Pandas, SQL.
• Practical experience with cloud-based ML platforms (AWS SageMaker, GCP AI Platform, Azure ML).
• Experience leading the use of AI-assisted development tools with validated outputs.
• Strong understanding of responsible AI, data handling, security, and resiliency practices.
• Proficient in SDLC and agile practices, including CI/CD and security.

Responsibilities

• Executes creative software solutions with the ability to think beyond routine approaches.
• Develops secure, high-quality production code and reviews code written by others.
• Drives enterprise AI-assisted engineering practices to improve quality, speed, and reliability.
• Applies SDLC tools and automation to improve value and efficiency.
• Identifies opportunities to automate remediation and improve stability of software.
• Leads evaluation sessions with vendors and teams to assess designs and fit.
• Designs and troubleshoots with consideration of upstream and downstream systems.

Skills

Python

ML frameworks

Spark/Pandas/SQL

Cloud ML platforms

AI-assisted development tools

CI/CD

Agile methodologies

Secure coding

Data analysis on large datasets

System design & debugging

Education

Formal training or certification in software engineering concepts

Tools

Docker

Kubernetes

Airflow

Snowflake

Databricks

Terraform

CloudFormation

Job description

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 Consumer & Community Banking, you are part of an agile team that works to enhance, design, and deliver the software components of the firm’s state-of-the-art technology products in a secure, stable, and scalable way. As an emerging member of a software engineering team, you execute software solutions through the design, development, and technical troubleshooting of multiple components within a technical product, application, or system, while gaining the skills and experience needed to grow within your role.

Job responsibilities:

• Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or breakdown technical problems
• Develops secure and high-quality production code, and reviews and debugs code written by others
• Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team.
• 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.
• Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems
• 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
• Designs, develops, codes, and troubleshoots with consideration of upstream and downstream systems and technical implications
• 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
• Applies technical troubleshooting to breakdown solutions and solve technical problems of basic complexity
• Gathers, analyzes, and draws conclusions from large, diverse data sets to identify problems and contribute to decision-making in service of secure, stable application development
• Learns and applies system processes, methodologies, and skills for the development of secure, stable code and systems

Required qualifications, capabilities, and skills:

• Formal training or certification on software engineering concepts and 3+ years applied experience
• Hands-on practical experience delivering system design, application development, testing, and operational stability
• Hands-on experience building, deploying, and maintaining machine learning platforms or infrastructure
• Proficiency in Python and one or more ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn). Experience with data processing frameworks and tools (e.g., Spark, Pandas, SQL)
• Practical experience with cloud-based ML platforms (e.g., AWS SageMaker, GCP AI Platform, Azure ML) or on-prem ML infrastructure
• Demonstrated experience leading effective use of approved AI-assisted software development tools (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 engineers on safe, compliant adoption within delivery practices
• Proficient in all aspects of the Software Development Life Cycle
• Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
• In-depth knowledge of the financial services industry and their IT systems
• Practical cloud native experience

Preferred qualifications, capabilities, and skills:

• Familiarity with Databricks for scalable data engineering and ML platform integration
• Experience working with Snowflake for cloud-based data warehousing and analytics
• Exposure to Snorkel AI for programmatic data labeling and training data management
• Experience with containerization and orchestration tools (e.g., Docker, Kubernetes, Airflow)
• Familiarity with feature stores, model registries, and ML metadata management
• Experience with infrastructure-as-code tools (e.g., Terraform, CloudFormation)
• Experience with RESTful APIs and microservices architectures