Lead Cybersecurity Architect

JPMorgan Chase & Co. • Jersey City, NJ

2d • $156,750 - $215,000

About The Position

As a Lead Architect (VP), you will provide independent oversight while partnering closely with engineering, product, and control stakeholders to embed resiliency-by-design into AI systems and delivery processes. You’ll help ensure that AI-enabled solutions—including modern GenAI/LLM workloads and MCP-based service integrations—meet enterprise security, resiliency, and regulatory expectations without slowing innovation.

The role focuses on establishing resilient, secure, and operationally ready AI platforms; enabling responsible production use of GenAI; assessing standards and remediation; and providing reusable guidance that teams can apply consistently. It requires partnering across business and platform teams and balancing governance with the pace of engineering delivery.

Requirements

• Significant experience designing, delivering, and operating enterprise-scale platforms across on-premises and cloud environments.
• Strong grounding in AI/ML engineering and production AI, including model lifecycle, data dependencies, reliability, performance, monitoring, drift, and change management.
• Hands-on understanding of GenAI/LLM systems and modern patterns such as RAG, agents, prompt/model evaluation, and safety controls, including how these workloads behave in production.
• Demonstrated strength in resiliency, availability, recovery, and data protection controls, especially for distributed systems and cloud-native services.
• Experience leveraging cloud AI and platform services such as AWS, Microsoft Azure, or Google Cloud and integrating managed services into governed enterprise environments.
• Ability to act as a strategic partner and influencer, driving alignment across engineering, product, risk, and control stakeholders.
• Excellent communication skills, including the ability to translate between architecture, risk/control requirements, and engineering execution and produce clear decisions, trade-offs, and documentation.

Nice To Haves

• Experience translating business objectives and governance/risk requirements into pragmatic engineering standards, reference architectures, and paved-road enablement patterns.
• Experience with Amazon Bedrock or equivalent enterprise model access platforms such as Azure OpenAI or Vertex AI, including identity, access control, and governance considerations.
• Experience with GenAI mediation patterns such as MCP or comparable governed tool/service routing, including auditability, policy enforcement, and controlled connectivity to internal or external services.
• Experience with Temporal or comparable workflow orchestration platforms for durable automation, long-running AI operations, and agent/workflow reliability.
• Experience with sandboxed execution, coding agents, secure agent runtimes, or developer workspaces for controlled code execution and experimentation.
• Experience with token/cost telemetry, usage attribution, chargeback/showback, or FinOps data pipelines for AI platform economics and capacity management.
• Experience supporting regulated, sensitive, or client-confidential workloads, including strong data-handling, privacy, and operational-risk practices.

Responsibilities

• Define, standardize, and drive patterns for high availability, disaster recovery, backup and restore, capacity planning, and operational readiness for AI/ML and GenAI services.
• Collaborate with Lines of Business and platform/service teams to influence architecture, controls, and operating models that support AI value realization and enablement at scale.
• Support teams in productionizing LLM-powered capabilities, including retrieval-augmented generation, agentic workflows, evaluation and monitoring, and safety guardrails, with reliability, traceability, and appropriate controls.
• Ensure AI solutions align with enterprise security, resiliency, and external regulatory expectations; identify gaps, define actionable remediation, and drive closure through accountable owners and timelines.
• Review solution designs, validate runbooks and SLOs/SLAs, and guide teams through readiness checkpoints, including testing, failover exercises, incident learnings, and continuous improvement.
• Create reusable guardrails, reference architectures, and enablement guidance that engineering teams can adopt consistently across environments.
• Translate architecture and risk/control requirements into clear decisions, trade-offs, and documentation.

Benefits

• Competitive total rewards package, including base salary determined by role, experience, skill set, and location.
• Eligible roles may receive commission-based pay and/or discretionary incentive compensation in cash and/or forfeitable equity.
• Comprehensive health care coverage.
• On-site health and wellness centers.
• Retirement savings plan.
• Backup childcare.
• Tuition reimbursement.
• Mental health support.
• Financial coaching.

What This Job Offers

• Job Type: Full-time
• Career Level: Executive
• Education Level: No Education Listed