Senior Full-Stack Engineer: AI‑Powered, Kubernetes‑Driven

JPMorganChase

San Francisco (CA)

On-site

USD 170,000 - 230,000

Full time

5 days ago
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Job summary

JPMorganChase is seeking a Lead Software Engineer – Full Stack to own end-to-end delivery of scalable, secure tech products within the Enterprise Technology team. You will work across frontend (React/TypeScript), backend (Python), data/workflow (Airflow) and DB (CockroachDB) in a fast, Agile environment.

You will lead architecture decisions, drive AI-assisted coding practices, ensure security and observability, and operate cloud-native deployments on Kubernetes with robust monitoring and

Qualifications

  • Formal training or certification on software engineering concepts and 5+ years applied experience.
  • Demonstrated full stack engineering capability across the SDLC.
  • Strong proficiency in Python and React with production-grade web apps.
  • Hands-on experience deploying on Kubernetes and with distributed databases.

Responsibilities

  • Owns end-to-end full stack delivery across frontend, backend, data and DB layers.
  • Designs scalable, highly available services and user experiences for large-scale apps.
  • Builds and maintains cloud-native deployments on Kubernetes with health checks and rollouts.
  • Drives observability and performance tuning using Splunk and Grafana.

Skills

Python
React
TypeScript
Kubernetes
Airflow
CockroachDB
APIs
CI/CD
Observability
AI-assisted development
Security
Kafka
DevOps

Education

Software engineering certification

Tools

Kubernetes
Airflow
CockroachDB
Splunk
Grafana
API gateways

Job description

JPMorganChase is seeking a Lead Software Engineer – Full Stack to own end-to-end delivery of scalable, secure tech products within the Enterprise Technology team. You will work across frontend (React/TypeScript), backend (Python), data/workflow (Airflow) and DB (CockroachDB) in a fast, Agile environment.

You will lead architecture decisions, drive AI-assisted coding practices, ensure security and observability, and operate cloud-native deployments on Kubernetes with robust monitoring and

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