Software Engineer III - AI/ML Developer

JP Morgan Chase; Plano (TX); On-site; USD 110,000 - 160,000; Full time

Job summary

JP Morgan Chase in Plano, TX is seeking a Software Engineer III to design, develop, and troubleshoot secure, scalable software components within Consumer & Community Banking. You will work on AI-assisted engineering practices, contribute to ML model deployment, and collaborate in an agile environment to deliver high-quality production-grade code.

The role requires hands-on experience with Python, ML frameworks, cloud ML platforms, and modern SDLC processes, with a focus on security, resiliency,

Qualifications

• 3+ years of applied software engineering experience.
• Experience delivering systems design, development, testing, and operational stability.
• Experience building ML platforms or infrastructure.
• Experience with Python and ML frameworks.
• Experience with cloud-based ML platforms or on-prem ML infra.
• Experience leading effective use of AI-assisted development tools.
• Strong understanding of responsible AI and secure engineering practices.

Responsibilities

• Executes creative software solutions and debugging across components.
• Develops secure, high-quality production code and reviews others' code.
• Drives AI-assisted engineering practices to improve quality, speed, and reliability.
• Applies SDLC tools and automation to increase value of automation.
• Identifies opportunities to automate recurring issues for stability.
• Leads evaluation sessions with vendors and internal teams on architecture.
• Designs and troubleshoots software with consideration of upstream/downstream systems.
• Gathers and analyzes large data sets to support secure, stable app development.
• Learns system processes to develop secure, stable code and systems.

Skills

Python

ML frameworks

Data processing tools

Agile methodologies

SDLC proficiency

Security & resiliency

AI-assisted development tools

Tools

TensorFlow

PyTorch

Spark

Pandas

SQL

Docker

Kubernetes

Airflow

Snowflake

Databricks

REST APIs

Terraform

CloudFormation

SageMaker

Azure ML

GCP AI Platform

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