Staff Engineer - Platform Engineering
New
IndiaFull-TimeStaff
Salary not disclosed
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Job Details
- Experience
- 9+ years
- Required Skills
- Node.jsGCPKubernetesGoCI/CDMicroservicesSaaSDistributed Systems
Requirements
- 9+ years of software engineering experience with demonstrated success building distributed systems or large-scale backend services
- Hands-on experience designing, optimizing, and scaling large-scale backend systems and data-intensive applications
- Strong understanding of distributed systems, microservices, APIs, CI/CD pipelines, and observability frameworks
- Experience leveraging AI-assisted engineering workflows and building systems/processes that improve SDLC effectiveness and engineering productivity
- Proven ability to lead technically, navigate ambiguity, and deliver impactful engineering outcomes
- Experience operating systems at high scale with a strong focus on performance, reliability, and resiliency
- Strong problem-solving skills with the ability to simplify complex technical challenges
Responsibilities
- Architect, develop, and maintain reusable frameworks, SDKs, and core platform services using Node.js and GoLang
- Build scalable, cloud-native solutions leveraging Google Cloud Platform (GCP)
- Design and optimize systems that efficiently handle large-scale data and high-throughput workloads
- Contribute to high-performance service architectures capable of handling massive scale with strong reliability and observability standards
- Lead technical design reviews, establish engineering best practices, and mentor senior engineers across teams
- Drive architectural decisions for scalability, performance, security, and maintainability
- Partner cross-functionally with product, infrastructure, and engineering teams to deliver reliable platform capabilities
- Improve developer productivity by building internal tooling, shared libraries, and scalable engineering foundations
- Lead initiatives that leverage AI effectively across engineering workflows, including code generation, testing, developer tooling, incident analysis, and SDLC automation
- Build and evolve systems, platforms, and engineering processes that improve SDLC efficiency, release velocity, reliability, and developer experience
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