React JS Developer
Builds React front-end applications and Camunda 7 BPMN workflow orchestration backed by Python (FastAPI/Flask) REST APIs and Java/Python workers, including agentic AI/LLM workflow steps and Databricks job automation. On-site role in Columbus, OH.
- Compensation
- Not disclosed
- Location
- Columbus, OH, USA
- Work setup
- Onsite
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- Not specified
- Category
- Not specified
- Posted
Skills
Must have
- Build and maintain React front-end applications (component-driven UI, hooks/state management, robust API consumption)
- Design and implement Camunda 7 BPMN workflows (service/user tasks, gateways, timers, message events)
- Develop Python REST APIs (FastAPI/Flask-style) with validation, secure auth, and downstream integrations
- Deliver API-centric orchestration via Camunda 7 External Tasks
- Build scalable Java/Python workers with idempotency, retries/backoff, and resilient REST integrations
- Integrate Agentic AI: orchestrate LLM/agent calls as governed workflow steps (tool/function calling, human-in-the-loop, auditability)
- Trigger/monitor Databricks jobs and operate Camunda via Cockpit/Tasklist/Admin
Full description
Build and maintain React (front-end) applications using component-driven UI, hooks/state management, and robust API consumption (auth-aware calls, error handling, pagination/caching) integrated with workflow-backed user journeys
Design and implement Camunda 7 BPMN workflows (service/user tasks, gateways, timers, message events) with controlled transaction boundaries and throughput tuning using asyncBefore/asyncAfter
Develop Python REST APIs (eg, FastAPI/Flask-style services) to expose workflow/data endpoints, enforce validation, implement secure auth patterns, and integrate with downstream systems
Deliver API-centric orchestration via Camunda 7 External Tasks, building scalable
Java/Python workers with idempotency, retries/backoff, and resilient REST integrations to external/internal services
Integrate Agentic AI capabilities by orchestrating LLM/agent calls as governed workflow steps (tool/function calling, prompt/version management, human-in-the-loop approvals, auditability) and automated analytics by triggering/monitoring Databricks jobs, correlating results back into Camunda and operating via Cockpit/Tasklist/Admin