Join us to engineer a trusted data platform that helps protect customers and the firm while enabling smarter, faster decisions, you’ll grow your skills alongside experienced engineers, collaborate across teams, and ship high-impact software that scales.
Job summary
As a Software Engineer III at JPMorgan Chase within the Corporate Sector, you serve as a seasoned member of an agile data engineering team, building and delivering a trusted Global Know Your Customer (KYC) and Risk Assessment Data Platform in a secure, stable, and scalable way, you leverage your technical capabilities and collaborate with colleagues across the organization to promote best-in-class outcomes across technologies that support one or more firm portfolios, you help uphold strong engineering practices and deliver high-impact software that scales across multiple teams.
Job responsibilities
- Develop secure, high-quality production code for data-intensive applications and platforms
- Create durable, reusable software frameworks and patterns leveraged across teams and functions
- Advise cross-functional teams on technological matters within your domain of expertise
- Apply knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve value realized by automation at scale
Required qualifications, capabilities, and skills
- Hands-on practical experience delivering system design, application development, testing, and operational stability at enterprise scale
- Expertise in one or more programming languages, particularly Python and/or Java
- Deep knowledge of software application development and technical processes, with considerable depth in one or more disciplines (for example, cloud, artificial intelligence/machine learning, or data engineering)
- Experience with large-scale data processing, microservices, API design, Kafka, Redis, Memcached, observability tools (Dynatrace, Splunk, Grafana), and orchestration frameworks (Airflow, Temporal)
- Working knowledge of relational and NoSQL databases, vector stores, data lake architectures, and data governance
- Practical cloud-native experience (AWS, Azure, or GCP)
- Ability to present and effectively communicate with senior leaders and executives
- 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.
Preferred qualifications, capabilities, and skills
- Experience with modern data platforms (e.g., Databricks, Snowflake) and building solutions on cloud-native data ecosystems.
- Strong hands-on big data engineering skills, including Spark/PySpark and related distributed processing technologies.
- Deep expertise in open table formats and metadata/catalog services, such as Apache Iceberg, for scalable, governed data management.
- Experience with large language model (LLM) orchestration frameworks and model serving/managed endpoint infrastructure (e.g., AWS Bedrock, Azure OpenAI).
- Proficient in enterprise-authorized AI-assisted development tools and responsible AI engineering practices—able to validate/refine AI outputs for correctness, performance, and security while guiding peers on safe, compliant usage.
Skills Required
- System design, application development, testing, and operational stability at enterprise scale
- Expertise in one or more programming languages, particularly Python and/or Java
- Deep knowledge of software application development and technical processes (cloud, AI/ML, or data engineering depth)
- Experience with large-scale data processing, microservices, and API design
- Experience with Kafka, Redis, Memcached
- Experience with observability tools (Dynatrace, Splunk, Grafana)
- Experience with orchestration frameworks (Airflow, Temporal)
- Working knowledge of relational and NoSQL databases, vector stores, data lake architectures, and data governance
- Practical cloud-native experience (AWS, Azure, or GCP)
- Ability to present and effectively communicate with senior leaders and executives
- Leverage enterprise-authorized AI coding assist tools and apply SDLC toolchain automation responsibly
- Experience with modern data platforms (Databricks, Snowflake)
- Strong hands-on big data engineering skills, including Spark/PySpark
- Deep expertise in open table formats and metadata/catalog services (Apache Iceberg)
- Experience with LLM orchestration frameworks and model serving/managed endpoint infrastructure (e.g., AWS Bedrock, Azure OpenAI)
- Proficiency in responsible AI engineering practices and validating AI outputs
JPMorganChase Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about JPMorganChase and has not been reviewed or approved by JPMorganChase.
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Healthcare Strength — Medical, dental, vision, and mental-health coverage are broad, with wellness incentives, on-site or virtual care, and an EAP offering coaching and counseling. Plan materials emphasize accessible options, including multiple medical choices and tools to manage costs.
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Parental & Family Support — Paid parental leave extends up to 16 weeks for all parents, supplemented by paid Critical Caregiver Leave. Family resources include backup childcare via Bright Horizons, lactation support and milk-shipping, family-building assistance, and even a free five-month SNOO rental for newborns.
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Retirement Support — Retirement programs include a 401(k) with an annual company match and automatic pay credits for most employees, with a legacy pension available to earlier hires. An Employee Stock Purchase Plan at a 5% discount further supports long-term savings.
JPMorganChase Insights
What We Do
JPMorgan Chase & Co. (NYSE: JPM) is a leading global financial services firm with assets of $3.7 trillion and operations worldwide. The firm is a leader in investment banking, financial services for consumers and small businesses, commercial banking, financial transaction processing, and asset management. A component of the Dow Jones Industrial Average, JPMorgan Chase & Co. serves millions of consumers in the United States and many of the world’s most prominent corporate, institutional and government clients under its J.P. Morgan and Chase brands. Technology fuels every aspect of our company and is at the heart of everything we do. With over 50,000 technologists globally and an annual tech spend of $12 billion, we are dedicated to improving the design, analytics, development, coding, testing and application programming that goes into creating high quality software and new products. Learn more about technology at our firm, explore resources from our Distinguished Engineers, AI & ML researchers, and other experts; access the latest episode of our TechTrends podcast, and more at www.jpmorgan.com/technology. Information about JPMorgan Chase & Co. is available at www.jpmorganchase.com. ©2023 JPMorgan Chase & Co. All rights reserved. JPMorgan Chase is an Equal Opportunity Employer, including Disability/Veterans.
Why Work With Us
Our technologists work on a diverse range of solutions that include strategic technology initiatives, big data, mobile, electronic payments, machine learning, cybersecurity, enterprise cloud development, and other state-of-the-art technologies.
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