Temporal Engineer

Temporal Engineer – 2 Years

Role Overview

We are looking for a Temporal Engineer with 2 years of hands-on experience in building and supporting workflow orchestration solutions using Temporal (or Cadence). The role will focus on designing workflows integrating Temporal into microservices-based applications and ensuring reliable execution of distributed systems. This position is ideal for engineers with solid backend or DevOps experience who have begun specializing in workflow orchestration.

Key Responsibilities

• Workflow Development & Integration

  • Design implement and maintain Temporal workflows and activities.

  • Collaborate with application teams to integrate workflows with microservices and data pipelines.

  • Support development in Go Java or Python for Temporal SDKs.

• Platform Management

  • Assist in configuring and managing Temporal clusters in dev test and production.

  • Monitor worker performance retries and error handling.

  • Support upgrades patches and scaling initiatives.

• Monitoring & Troubleshooting

  • Use observability tools (Prometheus Grafana ELK OpenTelemetry) for workflow monitoring.

  • Troubleshoot workflow failures latency and worker scaling issues.

  • Develop runbooks for common incidents.

• Collaboration & Support

  • Partner with DevOps and cloud teams to automate deployments of workflows.

  • Work with senior engineers to define best practices for Temporal usage.

  • Provide L2/L3 support for workflow-related issues.

Required Skills & Experience

• 2 years in backend engineering DevOps or workflow orchestration.

• 1–2 years of hands-on experience with Temporal (or Cadence).

• Strong programming skills in Go Java or Python.

• Understanding of distributed systems retries compensation logic and event-driven architectures.

• Familiarity with Docker Kubernetes and CI/CD pipelines.

Preferred Knowledge

• Exposure to data orchestration tools (Airflow Argo Workflows Prefect).

• Basic knowledge of Kafka RabbitMQ or event streaming platforms.

• Experience with cloud-native platforms (AWS GCP or Azure).

Education & Certifications

• Bachelor’s degree in Computer Science IT or related field.

• Preferred certifications: Kubernetes (CKA/CKAD) cloud certifications (AWS/GCP/Azure).

• Temporal training/certifications (if available) are an added advantage.