Software Engineer Ii Public Cloud & Big Data jobs at Jpmorgan in United States, Seattle

Job responsibilities

• Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems
• Develops secure high-quality production code, and reviews and debugs code written by others
• 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
• Leads communities of practice across Software Engineering to drive awareness and use of new and leading-edge technologies
• Adds to team culture of diversity, opportunity, inclusion, and respect
• Deliver AI/ML based solutions to improve Kubernetes platforms for JPMC
• Regularly provides technical guidance and direction to support the business and its technical teams

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 5+ years applied experience
• Hands-on practical experience delivering system design, application development, testing, and operational stability
• Advanced in one or more programming language(s)
• Proficiency in automation and continuous delivery methods
• Proficient in all aspects of the Software Development Life Cycle
• Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
• Demonstrated proficiency in software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.)
• In-depth knowledge of the financial services industry and their IT systems
• Practical cloud native experience
• Experience applying data engineering and machine learning techniques
• Experience in Generative AI, LLMs and AI Agents

• Experience working with modern private & public cloud infrastructure platforms - Kubernetes, AWS EKS Terraform, Ansible and other automation tools.
• Experience in multiple Cloud platforms like GCP GKE is a plus
• Knowledge of deep learning and ML Ops workflows
• Experience in Time Series analysis, including forecasting, anomaly detection, and trend analysis

As a
Applied AI ML Sr Associate at JPMorgan Chase within the Corporate Sector – AIML Data Platforms,you will lead a specialized technical area, driving impact across teams, technologies, and projects. In this role, you will leverage your deep knowledge of machine learning, software engineering, and product management to spearhead multiple complex ML projects and initiatives, serving as the primary decision-maker and a catalyst for innovation and solution delivery.

You will be responsible for hiring, leading, and mentoring a team of Machine Learning and Software Engineers, focusing on best practices in ML engineering, with the goal of elevating team performance to produce high-quality, scalable ML solutions with operational excellence. You will engage deeply in technical aspects, reviewing code, mentoring engineers, troubleshooting production ML applications, and enabling new ideas through rapid prototyping. Your passion for parallel distributed computing, big data, cloud engineering, micro-services, automation, and operational excellence will be key.

Job Responsibilities

• Architect and implement distributed AI/ML infrastructure, including inference, training, scheduling, orchestration, and storage.
• Integrate Generative AI and Classical AI within the ML Platform using state-of-the-art techniques.
• Implement, deliver, and support high-quality ML solutions in partnership with a team of ML Engineers.
• Collaborate with product teams to deliver tailored, AI/ML-driven technology solutions.
• Develop advanced monitoring and management tools for high reliability and scalability in AI/ML systems.
• Optimize AI/ML system performance by identifying and resolving inefficiencies and bottlenecks.
• Drive the adoption and execution of AI/ML Platform tools across various teams.
• Lead the entire AI/ML product life cycle through planning, execution, and future development by continuously adapting, developing new AI/ML products and methodologies, managing risks, and achieving business targets like cost, features, reusability, and reliability to support growth.

Required Qualifications, Capabilities, and Skills

• Bachelor's degree or equivalent practical experience in a related field.
• 6+ years of experience in engineering management with a strong technical background in machine learning.
• Extensive hands-on experience with AI/ML frameworks (TensorFlow, PyTorch, JAX, scikit-learn).
• Deep expertise in Cloud Engineering (AWS, Azure, GCP) and Distributed Micro-service architecture.
• Experienced with Kubernetes ecosystem, including EKS, Helm, and custom operators.
• Background in High Performance Computing, ML Hardware Acceleration (e.g., GPU, TPU, RDMA), or ML for Systems.
• Strategic thinker with the ability to craft and drive a technical vision for maximum business impact.

Preferred Qualifications, Capabilities, and Skills

• Strong coding skills and experience in developing large-scale AI/ML systems.
• Proven track record in contributing to and optimizing open-source ML frameworks.
• Understanding & experience of AI/ML Platforms, LLMs, GenAI, and AI Agents.

As a Technology Auditor - Associate within the Asset & Wealth Management (AWM) Technology Audit Team, you will execute the annual audit plan, participate in audit engagements by performing audit testing, and participate in various continuous monitoring efforts. This position is ideal for someone with knowledge of various technologies, operating systems, databases and data analytical skills, as well as the audit and risk skills to be able to effectively execute global technology audits.

Job responsibilities

• Participate on technology audit engagements, from planning to reporting, and produce quality deliverables to both department and professional standards, while ensuring audits are completed timely and within budget.
• Work closely with global Audit colleagues in the early identification of emerging control issues, and report them in a timely manner to Audit management and business stakeholders
• Partner with stakeholders, business management, other control groups (i.e. risk management, compliance, fraud prevention), establishing strong working relationships while maintaining independence
• Finalize audit findings and use judgment to provide an overall opinion on the control environment by developing recommendations to strengthen internal controls
• Communicate audit findings to management, and identify opportunities for improvement in the design and effectiveness of key controls
• Stay up-to-date with evolving industry/regulatory changes impacting the business and participate in appropriate control forums
• Find ways to drive efficiency with existing technical infrastructure through automation while embracing the innovative opportunities offered by new technologies
• Recognize the confidential nature of Internal Audit communications and access to information; exercise discipline in protecting the confidentiality and security of information in accordance with firm policy.

Required qualifications, skills and capabilities

• Knowledge and experience in various Technology and Cyber domains, for e.g., Software Lifecycle Development (SDLC), Vulnerability Management, Change Management, etc.
• Understanding of internal control concepts, with proven ability to evaluate and determine the adequacy of controls by considering business and technology risks in an integrated manner.
• Strong data analytical skills with extensive experience and ease of use with industry-leading data analytics tools such as Alteryx and Tableau.
• Strong analytical skills, particularly with regards to assessing the probability and impact of an internal control weakness.
• Excellent written, verbal, and presentation skills; adept at presenting complex and sensitive issues to senior management and strong interpersonal and influencing skills, with the ability to establish credibility and build partnerships with senior business and control partners.
• Enthusiastic and self-motivated, with a keen interest in learning; effective under pressure and willing to take personal responsibility/accountability as well as flexible to changing business priorities and ability to multitask in a constantly changing environment.

Preferred qualifications, skills and capabilities

• Experience with internal audit methodology and applying concepts in audit delivery and execution preferred.
• Certified in CISA, CISM or other technology audit certifications.
• Bachelor's degree in Technology or related field
• Preferred internal or external technology auditing experience, or relevant technology risk and control management experience.

As a
Applied AI ML Lead at JPMorgan Chase within the Corporate Sector – AIML Data Platforms, you will lead a specialized technical area, driving impact across teams, technologies, and projects. In this role, you will leverage your deep knowledge of machine learning, software engineering, and product management to spearhead multiple complex ML projects and initiatives, serving as the primary decision-maker and a catalyst for innovation and solution delivery.

You will be responsible for hiring, leading, and mentoring a team of Machine Learning and Software Engineers, focusing on best practices in ML engineering, with the goal of elevating team performance to produce high-quality, scalable ML solutions with operational excellence. You will engage deeply in technical aspects, reviewing code, mentoring engineers, troubleshooting production ML applications, and enabling new ideas through rapid prototyping. Your passion for parallel distributed computing, big data, cloud engineering, micro-services, automation, and operational excellence will be key.

Job Responsibilities

• Lead and manage a team of machine learning engineers, ensuring the implementation, delivery, and support of high-quality ML solutions.
• Collaborate with product teams to deliver tailored, AI/ML-driven technology solutions.
• Architect and implement distributed AI/ML infrastructure, including inference, training, scheduling, orchestration, and storage.
• Develop advanced monitoring and management tools for high reliability and scalability in AI/ML systems.
• Optimize AI/ML system performance by identifying and resolving inefficiencies and bottlenecks.
• Drive the adoption and execution of AI/ML Platform tools across various teams.
• Integrate Generative AI and Classical AI within the ML Platform using state-of-the-art techniques.
• Lead the entire AI/ML product life cycle through planning, execution, and future development by continuously adapting, developing new AI/ML products and methodologies, managing risks, and achieving business targets like cost, features, reusability, and reliability to support growth.
• Manage, mentor, and develop a team of AI/ML professionals in a way that promotes a culture of excellence, continuous learning, and supports their professional goals.

Required Qualifications, Capabilities, and Skills

• Bachelor's degree or equivalent practical experience in a related field.
• 8+ years of experience in engineering management with a strong technical background in machine learning.
• Extensive hands-on experience with AI/ML frameworks (TensorFlow, PyTorch, JAX, scikit-learn).
• Deep expertise in Cloud Engineering (AWS, Azure, GCP) and Distributed Micro-service architecture.
• Experienced with Kubernetes ecosystem, including EKS, Helm, and custom operators.
• Background in High Performance Computing, ML Hardware Acceleration (e.g., GPU, TPU, RDMA), or ML for Systems.
• Strategic thinker with the ability to craft and drive a technical vision for maximum business impact.
• Demonstrated leadership in working effectively with engineers, data scientists, and ML practitioners.

Preferred Qualifications, Capabilities, and Skills

• Strong coding skills and experience in developing large-scale AI/ML systems.
• Proven track record in contributing to and optimizing open-source ML frameworks.
• Recognized thought leader within the field of machine learning.
• Understanding & experience of AI/ML Platforms, LLMs, GenAI, and AI Agents.