Principal Software Engineer - Platform
J
JobgetherEnterprise AI SaaS
Based in IndiaFull-TimePrincipal
Salary not disclosed
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Job Details
- Experience
- 10+ years
- Required Skills
- KubernetesSaaSDistributed Systems
Requirements
- 10+ years of experience in platform engineering, infrastructure engineering, backend systems, or related disciplines within SaaS environments.
- Proven experience designing and building enterprise-scale distributed systems and highly available production platforms.
- Deep expertise in multi-tenant architectures and tenant isolation strategies.
- Strong hands-on knowledge of Kubernetes, containerization, and cloud infrastructure across AWS, GCP, or Azure.
- Strong understanding of distributed systems patterns, including service meshes, event-driven architectures, and workflow orchestration.
- Demonstrated ability to drive multi-quarter technical initiatives from concept through production deployment at scale.
- Strong ability to write and maintain production-quality code while leveraging modern AI-assisted development tools.
- Experience designing contract-driven or schema-first data platforms is highly valuable.
- Familiarity with Temporal or comparable workflow orchestration technologies is advantageous.
- Experience supporting enterprise workloads subject to strict security, privacy, or compliance requirements.
- High-agency mindset with the ability to take ownership of ambiguous and technically complex problems.
- Strong asynchronous communication skills and the ability to influence technical decisions without relying on formal authority.
Responsibilities
- Design and build enterprise-scale platform services, including APIs, infrastructure components, runtime systems, and data ingestion frameworks.
- Architect context-storage capabilities that bring together structured, unstructured, vector, and graph data for AI-ready applications and systems.
- Solve complex multi-tenant architecture, tenant isolation, scalability, and reliability challenges within enterprise SaaS environments.
- Design and establish data contracts governing ingestion, validation, processing, routing, storage, and serving across heterogeneous systems.
- Own and evolve critical shared infrastructure spanning lakehouse technologies, vector stores, graph databases, and OLTP systems.
- Drive technical standards and architectural direction through RFCs, architecture reviews, technical documentation, and engineering best practices.
- Lead complex, multi-quarter technical initiatives from initial concept and architecture through production deployment and scale.
- Debug and resolve distributed systems issues across Kubernetes, workflow orchestration platforms, microservices, and cloud infrastructure.
- Mentor senior engineers and act as a technical force multiplier across engineering teams.
- Adopt and advance AI-native engineering practices, including the effective use of AI-assisted development tools.
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