Principal Cybersecurity Architect - Data Security jobs at Jpmorgan in United States, Washington, Seattle

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.

Job Responsibilities:

• Provide architecture and support for the adoption and management of Access Management, Directory & Federation Services, Single Sign-On (SSO), Multi-factor Authentication (MFA), and similar secure authentication services.
• Lead the development and maintenance of the Identity Management Controls, ensuring alignment with industry best practices.
• Develop, build, and maintain technology design and architecture to enable continuous contextual authentication and authorization, fostering innovation and continuous improvement.
• Mentor junior team members and lead cross-functional teams to drive cybersecurity initiatives and projects.
• Engage with stakeholders across various technical and business functions to develop and maintain the roadmap for enterprise IAM solutions, ensuring alignment with strategic goals.
• Conduct risk assessments and manage cybersecurity risks, implementing effective mitigation strategies.
• Maintain up-to-date knowledge of identity and access management best practices and encourage continuous learning and professional development within the team.

Required Qualifications, Capabilities, and Skills:

• Formal training or certification on Cybersecurity Architecture concepts and 5+ years applied experience
• Demonstrated design and development experience in large-scale, complex environments with heavy regulatory needs.
• Expertise in Authentication and Authorization protocols, including Active Directory Services, EntraID, ADFS, OAuth, OIDC, SAML, Encryptions, and PKI.
• Hands-on experience delivering Directory services security, Large scale migrations.
• Expertise in Digital Certificate Management (DCM) and rolling out PKI services across enterprise services
• Advanced proficiency in one or more programming languages and object-oriented programming (e.g., Python, Go).
• Proficiency in automation, continuous delivery methods (CI/CD), and Infrastructure as Code (IaC).
• Strong understanding of agile methodologies, application resiliency, and security.
• In-depth knowledge of the financial services industry and their IT systems.
• Experience in directory services and identity data management.

Preferred Qualifications, Capabilities, and Skills:

• Strong skills in cybersecurity, architecture, and process engineering.
• Excellent collaboration, communication, and stakeholder management skills.
• Experience with third-party tools and technologies, including ADFS, Active Directory, Microsoft Entra ID, ForgeRock, Ping Identity/Access, API Gateways, Active Directory, CyberArk, Delinea, and Hashi Corp Vault.

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.

Job responsibilities

• Utilizes public cloud services to build data and knowledge management services for GenAI engineering.
• Explores new and emerging technologies.
• Proactively identifies hidden problems and patterns in data and uses these insights to drive improvements.
• Executes software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build novel solutions or break down technical problems.
• Produces architecture and design artifacts for complex applications. Creates secure and high-quality production code and with limited guidance.
• Gathers and analyzes large, diverse data sets to identify problems and contribute to decision-making in service of secure, stable application development
• Adds to team culture of diversity, equity, inclusion, and respect.

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 2+ years applied experience
• 2+ years of professional experience in building products.
• Experience with public cloud services such as AWS or Azure
• Proficient in Java or Python
• Experience with Maven, microservices, GIT, REST, SQL, messaging and events, Software Development Life Cycle (SDLC), CI/CD, resiliency, and security.
• Practical experience in system design, application development, testing, and operational stability in a large corporate environment

Preferred qualifications, capabilities, and skills

• Experience in developing technology products from start-up to scale-up, achieving product maturity, and ensuring operational stability.
• Experience with Caching; Spark; Big Data storage, processing, and consumption.
• Familiarity with GenAI, LLM and agentic orchestration frameworks, Retrieval-augmented generation (RAG), prompt engineering.
• Familiarity with data services: database, data warehouses, data lakes, vectordb, nosql db, graphdb

• Familiarity with search: semantic, TF-IDF, BM25, hybrid, efficient filtering.

Job responsibilities

• Leads multiple technology and process implementations across departments to achieve firmwide technology objectives
• Directly manages multiple areas with strategic transactional focus
• Provides leadership and high-level direction to teams while frequently overseeing employee populations across multiple platforms, divisions, and lines of business
• Acts as the primary interface with senior leaders, stakeholders, and executives, driving consensus across competing objectives
• Manages multiple stakeholders, complex projects, and large cross-product collaborations
• Influences peer leaders and senior stakeholders across the business, product, and technology teams
• Champions the firm’s culture of diversity, equity, inclusion, and respect
• Lead the development of AI/ML-centered EKS, Ray, EMR, Notebooks, and Studios that are tailored towards data scientists and ML/AI engineers.
• Act as a primary engineering leader with third-party stakeholders and internal stakeholders.
• Elevate the overall engineering culture and practices across the organization and the firm.
• Represent the organization through external and internal talks and conferences.

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 10+ years applied experience. In addition, 5+ years of experience leading technologists to manage, anticipate and solve complex technical items within your domain of expertise
• Experience developing or leading large or cross-functional teams of technologists
• Demonstrated prior experience influencing across highly matrixed, complex organizations and delivering value at scale
• Experience leading complex projects supporting system design, testing, and operational stability
• Experience with hiring, developing, and recognizing talent
• Extensive practical cloud native experience
• Expertise in Computer Science, Computer Engineering, Mathematics, or a related technical field
• Bachelor's degree in Computer Science or equivalent practical experience.
• 5 years of experience working with Machine Learning, AI, Large Language Models (LLM) infrastructure, especially with training, model development, and other requests.
• Experience operating in a hyper-growth entrepreneurial environment, scaling new and emerging products from the ground up.

Preferred qualifications, capabilities, and skills

• Experience working at code level
• M.Sc or Ph.D in CS or any related field.
• Expertise in Machine Learning frameworks like Python, Scikit-learn, PyTorch, TensorFlow, Apache Spark, and experience with Generative AI models like GANs, Transformers, and Diffusion Models.
• Knowledge of MLOps best practices around model training, evaluation, deployment, and governance. Ability to communicate and help clients operationally set up MLOps functions.
• Experience integrating ML solutions with cloud platforms like AWS SageMaker, GCP Vertex AI, Azure Cognitive Services, and leveraging their pre-built capabilities.
• Proficiency in ML workflow tools like Kubeflow and MLflow for experiment tracking, model management, and model serving.
• Ability to identify and articulate the business value of AI/ML to stakeholders using innovative techniques like AI Readers, AI Assistants, Agentic frameworks, etc.
• Strong communication, presentation, and storytelling skills to influence technical sales cycles with business decision-makers.
• Passion for AI/ML and ability to stay updated on the latest advancements through conferences, publications, cohorts, etc. Experience in consulting, sales engineering, and/or customer success.
• Comfortable in evangelizing and marketing ML/AI practice with internal teams, partners, and customers alike.

Job responsibilities

• Provide thought leadership for securing on premise and cloud based AI/ML solution architecture
• Design comprehensive security architectures for cloud infrastructure projects
• Design secure networks and systems based on industry standards and best practices
• Identify and address security vulnerabilities, security risks, and other compliance issues
• Perform regular audits of all cloud infrastructure
• Participate in application and system hardening activities
• Develop and document security policies, procedures, and processes
• Conduct security risk assessments using various tools and processes
• Create and communicate threat models
• Partner with product managers to identify, quantify, and communicate all security risks.
• Drive innovation and ensure that JPMC maximizes the business benefits while minimizing security risk across your product

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 10+ years applied experience
• Advanced Technical knowledge in architecting, designing, and Integrating security solutions in a large-scale enterprise of highly distributed applications
• Experience designing/delivering secure cloud infrastructure architectures for our enterprise AI/ML applications
• Strong knowledge of AI/ML security concepts, threats, and vulnerabilities including Generative AI and Large Language Models
• Demonstrated proficiency in software applications and technical processes within artificial intelligence and/or machine learning.
• Practical cloud native experience with an understanding of cloud computing concepts and services such as AWS, Azure, GCP, etc
• Hands-on practical experience with Threat Models.
• Advanced in one or more programming languages
• Advanced understanding of agile methodologies such as continuous integration and delivery, application resiliency, and security
• Ability to evaluate current and emerging technologies to recommend the best solutions for the future state architecture
• Ability to present and effectively communicate with senior leaders and executives

Preferred qualifications, capabilities, and skills

• Knowledge of networking protocols and techniques, such as TCP/IP, routing, DNS, DHCP, etc.
• Knowledge of IAM concepts, including but not limited to: provisioning, RBAC, ABAC, SCIM, LDAP, federated identity platforms/products and Privileged Access Management
• Experience with API security and public cloud API integration
• Experience developing and understanding information security architecture, mitigation of threats, and compensating controls.
• Deep familiarity with frameworks such as NIST 800-53, OWASP, CVSS, the MITRE ATT&CK framework, MITRE Atlas, PCI, and Gramm-Leach-Bliley Act (GLBA).
• Experience using cloud Infrastructure as Code (IaC) using frameworks like Terraform
• Experience with microservices designs and implementations including docker, Kubernetes, helm

Job Responsibilities:

• Provide architecture and support for the adoption and management of Access Management, Directory & Federation Services, Single Sign-On (SSO), Multi-factor Authentication (MFA), and similar secure authentication services.
• Lead the development and maintenance of the Identity Management Controls, ensuring alignment with industry best practices.
• Develop, build, and maintain technology design and architecture to enable continuous contextual authentication and authorization, fostering innovation and continuous improvement.
• Mentor junior team members and lead cross-functional teams to drive cybersecurity initiatives and projects.
• Engage with stakeholders across various technical and business functions to develop and maintain the roadmap for enterprise IAM solutions, ensuring alignment with strategic goals.
• Conduct risk assessments and manage cybersecurity risks, implementing effective mitigation strategies.
• Maintain up-to-date knowledge of identity and access management best practices and encourage continuous learning and professional development within the team.

Required Qualifications, Capabilities, and Skills:

• Formal training or certification on Cybersecurity Architecture concepts and 5+ years applied experience
• Demonstrated design and development experience in large-scale, complex environments with heavy regulatory needs.
• Expertise in Authentication and Authorization protocols, including Active Directory Services, ADFS, OAuth, OIDC, SAML, Encryptions, and PKI.
• Hands-on experience delivering Directory services security, Large scale migrations.
• Expertise in Digital Certificate Management (DCM) and rolling out PKI services across enterprise services
• Advanced proficiency in one or more programming languages and object-oriented programming (e.g., Python, Go).
• Proficiency in automation, continuous delivery methods (CI/CD), and Infrastructure as Code (IaC).
• Strong understanding of agile methodologies, application resiliency, and security.
• In-depth knowledge of the financial services industry and their IT systems.
• Experience in directory services and identity data management.

Preferred Qualifications, Capabilities, and Skills:

• Strong skills in cybersecurity, architecture, and process engineering.
• Excellent collaboration, communication, and stakeholder management skills.
• Experience with third-party tools and technologies, including ADFS, Active Directory, Microsoft Entra ID, ForgeRock, Ping Identity/Access, API Gateways, Active Directory, CyberArk, Delinea, and Hashi Corp Vault.