Software Engineer [Multiple Positions Available]

JPMorgan Chase & Co.
Plano, United States of America
yesterday

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English

Job location

Plano, United States of America

Tech stack

Java
JavaScript
Agile Methodologies
Airflow
Amazon Web Services (AWS)
Automation of Tests
Azure
Big Data
C Sharp (Programming Language)
Cloud Database
Cloud Engineering
Code Coverage
Software Quality
Computer Engineering
Continuous Integration
Information Engineering
ETL
Data Security
Data Visualization
Distributed Computing Environment
Django
Elasticsearch
JUnit
Python
Machine Learning
Modular Design
Node.js
NumPy
Performance Tuning
Software Architecture
Query Optimization
TensorFlow
Software Engineering
Spinnaker
Systems Integration
Unstructured Data
Web Services
Data Logging
Test Driven Development
Postman
PyTorch
Istio
Flask
Delivery Pipeline
Database Optimization
Indexer
GIT
FastAPI
Pandas
Matplotlib
Pytest
Containerization
PySpark
Scikit Learn
Kubernetes
Information Technology
Apache Flink
Data Analytics
Amazon Web Services (AWS)
Integration Frameworks
Real Time Data
Plotly
Kafka
Linkerd (Service Mesh)
Operational Systems
Machine Learning Operations
REST
Stream Processing
Jenkins
Programming Languages
Microservices

Job description

Duties: Lead and manage a team of software engineers in designing, developing, and deploying enterprise-scale financial applications and data-driven platforms. Make architectural decisions across distributed, cloud- native, and microservices-based systems to ensure scalability, resiliency, and security. Provide technical leadership in implementing multi-cloud strategies, focusing on developer services. Drive adoption of data engineering and orchestration tools for distributed processing, Apache Kafka and Apache Flink for real-time data streaming, and Airflow/Prefect for workflow automation. Oversee integration of machine learning solutions into production systems, leveraging TensorFlow and PyTorch for model development, training, optimization, and deployment. Implement MLOps frameworks for end-to-end machine learning lifecycle management, including deployment, monitoring, and governance of models in production. Implement service mesh technologies to secure and optimize microservices communication within Kubernetes environments. Implement search and indexing technologies to support real-time data retrieval and high- performance search. Collaborate with cross-functional teams (product managers, data scientists, infrastructure engineers) to align technology initiatives with business objectives. Establish and enforce best practices in Agile SDLC, code quality, CI/CD automation, test-driven development, and observability (monitoring, logging, tracing) Manage project budgets, timelines, and risks while ensuring compliance with regulatory and security standards. Mentor and coach engineers to build technical expertise and leadership capability within the team.

Requirements

Minimum education and experience required: Bachelor's degree in Computer Science, Information Technology, Computer Engineering, Computer Information Systems, Information Technology, Data Engineering, or related field of study plus 7 years of experience in the job offered or as Software Engineer, Developer, IT Consultant or related occupation.

Skills Required: This position requires experience with the following: leading and managing software engineering teams, including mentoring, hiring and performance evaluation; designing and implementing microservice- based application and infrastructure architectures on AWS, including containerized workloads using ECS, Fargate, and Lambda, and service mesh technologies including Istio to ensure scalability, reliability, and operational efficiency; developing and maintaining end-to-end data engineering workflows using orchestration tools such as Apache Airflow or Prefect, data processing frameworks including PySpark and Kafka, and cloud-based data services to automate ingestion, transformation, and integration of structured and unstructured datasets; Python and its libraries and frameworks; working with large-scale enterprise data, including financial, operational, and behavioral datasets, used for analytics, reporting, and data-driven decision-making including Pandas, NumPy and PySpark; developing and deploying machine learning and AI applications using frameworks including TensorFlow, PyTorch, and scikit-learn, including integrating pre-trained models, performing evaluation and tuning, and managing deployment workflows through platforms such as MLflow or Kubeflow; designing and developing data visualizations using tools including Matplotlib, Seaborn, and Plotly to present analytical results, model insights, and key performance metrics to technical and business stakeholders; designing and developing RESTful APIs and web services using frameworks including FastAPI, Flask, and Django, including API integration, performance optimization, and secure data access controls; designing, implementing, and managing orchestration and ETL pipelines using tools such as Airflow, Prefect, or AWS Step Functions to automate ingestion, transformation, validation, and loading of data into analytical or operational systems; Utilizing MLOps frameworks such as MLflow or Kubeflow for ML model deployment, monitoring, and governance; Utilizing service mesh technologies such as Istio or Linkerd for microservices management and observability; using search and indexing technologies such as Elasticsearch, OpenSearch, or Algolia for managing and querying large datasets, including schema design, indexing strategies, and query optimization; developing software solutions using programming languages and frameworks including Python, Java, Node.js, JavaScript, and C#, emphasizing modular design, scalability, and CI/CD integration using Jenkins, Jules, and Spinnaker; designing and managing CI/CD pipelines such as Jenkins, Git, Code Pipeline, or Azure DevOps; applying software testing methodologies including unit, integration, regression, performance, and automated testing; implementing testing frameworks such as PyTest, JUnit, or Postman; integrating test coverage into CI/CD pipelines to ensure reliability and code quality.

Job Location: 8181 Communications Parkway, Plano, TX 75024.

Full-Time.

Benefits & conditions

We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.

About the company

JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world's most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management.

Apply for this position