Location: For deployment in Singapore; Visa Sponsorship is available

Our client is looking for a skilled Python Developer to join their team for a 12-month engagement. The successful candidate will play a pivotal role in the deployment and scaling of containerized workloads, utilizing Kubernetes and advanced observability tools. You will be responsible for managing the entire CI/CD lifecycle, ensuring high-performance, resilient systems through robust engineering practices.

Technical Requirements

• Experience: 5+ years of Python development.
• Core Competencies:
• Strong proficiency in Python programming language.
• Hands-on experience with Kubernetes (deploying, managing, and scaling containerized workloads).
• Strong background in observability, utilizing tools like Grafana, Prometheus, metrics, logs, traces, and alerting.
• Experience with CI/CD tools (Git, Jenkins, GitHub Actions, TeamCity).
• Expertise in scripting languages (Shell, Regular Expressions).
• Working knowledge of Linux administration and troubleshooting.
• Familiarity with open-source frameworks/libraries relevant to backend and platform development.
• Methodology:
• Experience with Test-Driven Development (TDD).
• Proficiency in Agile methodology (sprint planning, daily scrum, retrospectives, etc.).
• Bonus/Exposure:
• Awareness of Docker, Ansible, Splunk/SIEM, and Public Cloud platforms.
• Exposure to proxy, networking, or identity/authentication concepts (JWT, OAuth, SPIFFE) is a plus.

Project Milestones & Responsibilities. The role involves delivering critical outcomes across six key milestones:

1. Observability & Initial Setup: Deploy solutions in Dev/QA/UAT, establish logging, monitoring, SIEM integration, and draft initial runbooks.
2. Production Deployment: Deploy the Slipstream solution to Production, build/maintain automated CI/CD pipelines, and enable SRE monitoring dashboards.
3. Scalability: Roll out Slipstream across multiple Kubernetes clusters, extend deployments to Windows/Linux, and standardize configuration patterns.
4. Performance & Resiliency: Implement traffic-based autoscaling, enhance observability with alerts, and conduct stability/resiliency validation.
5. Optimization: Continuous analysis of production telemetry, performance benchmarking, and fine-tuning resource utilization and latency.
6. Documentation & Knowledge Transfer: Prepare technical/operational architecture documentation, create onboarding guides for consumer teams, and conduct training workshops.