Senior Lead Architect-enterprise Architecture

JPMorgan Chase JPMorgan Chase · Banking · Jersey City, NJ +1 · Corporate Sector

This role is for a Senior Lead Architect in Enterprise Architecture at JPMorgan Chase, focusing on shaping technology platforms, defining architectures, and ensuring resilient system design. The role involves leading solution design from concept to production, managing technical risks, and embedding reliability NFRs. It also includes identifying automation opportunities and defining AI/ML integration patterns within guardrails. The required skills include extensive software engineering experience, back-end and front-end development, data platform knowledge, and familiarity with resiliency patterns, observability, and CI/CD practices. Experience with AI/ML tooling for productivity and operations automation is preferred.

What you'd actually do

  1. Define target and transitional architectures and set practical guardrails for resiliency across application, data, and integration layers
  2. Lead solution design from concept to production, creating ADRs, HLDs, and LLDs that align to enterprise reference architectures and controls
  3. Run or contribute to design councils, perform architecture/design reviews, and manage exceptions and technical risk with clear remediation plans
  4. Guide implementation details (service boundaries, API contracts, data models, error handling, idempotency, failure modes, back-pressure)
  5. Ensure designs include HA/DR, observability (logs/metrics/traces), and capacity/performance considerations, and are ready for chaos and DR testing

Skills

Required

  • software engineering concepts
  • Java/Spring
  • REST
  • Python
  • messaging
  • caching
  • React
  • micro-frontends (MFEs)
  • performance/error boundary patterns
  • relational databases
  • graph databases
  • data lake implementations
  • HLDs/LLDs
  • resiliency patterns
  • observability and reliability practices
  • CI/CD
  • infrastructure as code
  • containerization/orchestration
  • secure SDLC practices
  • AI/ML tooling

Nice to have

  • AI/ML for operations automation
  • anomaly/outlier detection
  • predictive capacity
  • root-cause hints
  • agentic runbook execution
  • Python or Scala for data/ML use cases
  • model operationalization
  • responsible-AI guardrails
  • cloud data platforms
  • hybrid architectures
  • data governance and lineage
  • financial services
  • regulated environments
  • mission-critical systems
  • TOGAF
  • cloud certifications
  • SRE certifications

What the JD emphasized

  • resiliency
  • HA/DR
  • observability
  • resiliency NFRs
  • RTO/RPO, SLO/SLI, MTTR
  • AI/ML integration patterns
  • security, privacy, and model risk guardrails
  • regulated environments