Responsibilities
- Create and sustain robust backend systems, including APIs and microservices, suitable for production environments.
- Build asynchronous processing workflows, event-based architectures, and background task processors.
- Establish and uphold architectural standards for backend development, covering API design, service separation, data structures, and error management.
- Partner with product and feature teams to develop and deliver reusable platform components such as authentication, notifications, and third-party integrations.
- Incorporate AI agents into software development processes as functional tools to enhance productivity and code integrity.
- Help design and implement internal AI-powered development tools by creating the underlying infrastructure, APIs, and platform layers for LLM-based applications.
- Engage with large language models through prompt optimization, API integration, and building dependable inference pipelines.
- Maintain and advance Kubernetes-based infrastructure, managing Helm charts, workload settings, role-based access controls, and cluster administration.
- Develop standardized CI/CD pipeline configurations used across engineering teams, including stages for building, testing, security checks, and deployment.
- Build internal platform tools that empower engineers with self-service deployment and faster release cycles.
- Lead the adoption of observability standards using platforms such as Datadog, OpenTelemetry, and Prometheus for monitoring and diagnostics.
Work Arrangement
Hybrid
