Demo

Software Engineer III- AIML

JPMorgan Chase
Jersey, NJ Full Time
POSTED ON 1/7/2025
AVAILABLE BEFORE 3/6/2025

 

Bring your Software Engineering AIML experience and be an integral part of an agile team that's constantly pushing the envelope to enhance, build, and deliver top-notch technology products.

The Chief Data & Analytics Office (CDAO) at JPMorgan Chase is responsible for accelerating the firm’s data and analytics journey. This includes ensuring the quality, integrity, and security of the company's data, as well as leveraging this data to generate insights and drive decision-making. The CDAO is also responsible for developing and implementing solutions that support the firm’s commercial goals by harnessing artificial intelligence and machine learning technologies to develop new products, improve productivity, and enhance risk management effectively and responsibly.

As a Software Engineer III at JPMorgan Chase within the Corporate Sector, AIML Data Platforms Team Chief Data & Analytics office (CDAO), you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. In this role as a Software Engineer, you will drive significant business impact through your capabilities and contributions and apply deep technical expertise and problem-solving methodologies to tackle a diverse array of challenges that span multiple technologies and applications.

Job responsibilities

  • Solves the companies most challenging cloud data platform problems by building innovative technical solutions around Data Lake Tools.
  • Designs, implements, and maintains a managed AWS Databricks platform, and providing engineering and operational support.
  • Adds features to and refactors existing code in Infra as Code - terraform modules, API development with Python and/or other tech products.
  • Performs platform design, set-up and configuration, workspace administration, resource monitoring, providing engineering support to data engineering teams, Data Science/ML, and Application/integration teams.
  • Collaborates closely with the Team Leads, other Platform/Architecture teams and Data Engineers/Scientists/Architects/Modelers/Analysts to design technical solutions for AWS Databricks platform.
  • Drives decisions that influence the product design, application functionality, and technical operations and processes
  • Serves as a function-wide subject matter expert in one or more areas of focus
  • Influences peers and project decision-makers to consider the use and application of leading-edge technologies
  • Adds to the team culture of diversity, equity, inclusion, and respect

 

Required qualifications, capabilities, and skills

  • Formal training or certification on software engineering concepts and 3 years applied experience 
  • Programming experience in one or more of the following Java or Python
  • Hands-on experience in AWS Cloud Services Provisioning and Usage: RDS, Dynamo DB, Lambdas, IAM Role, EMR, EKS, Security Groups
  • Hands-on experience in Terraform Enterprise, CI/CD pipelines using Jenkins and Groovy
  • Good understanding of Networking Rules / Firewalls / DNS / IPv4 / Oauth / SAML / VPCs in AWS and On-Prem Systems, Big Data Compute Engines (Spark)
  • Cyber security fundamentals and working knowledge
  • Experience in designing, developing, or maintaining production-grade cloud solutions in Cloud ecosystems such as Amazon Web Services
  • Hands-on practical experience delivering system design, application development, testing, and operational stability
  • Ability to tackle design and functionality problems independently with little to no oversight
  • Experience in Computer Science, Computer Engineering, Mathematics, or a related technical field

Preferred qualifications, capabilities, and skills

  • Exposure to AWS & Databricks Platform/Infrastructure administration
  • Experience with Big Data Compute Engine - Spark
  • Experience with Agile development processes, as needed (SCRUM/KANBAN) using JIRA.
  • Experience in managing product release lifecycle at enterprise level.

 

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