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Freshworks is seeking a Principal Engineer to lead the design and evolution of enterprise-scale platform architecture across its multi-tier SaaS products. This is a hands-on technical leadership role combining deep systems expertise with strategic influence across multiple engineering teams.
You will own the platform architecture roadmap for a major domain, defining the target state and realistic path to modernization. Key responsibilities include designing scalable, secure, and cost-efficient architectures for high-throughput, low-latency, multi-tenant workloads; establishing architecture standards and decision-making practices; and evaluating emerging technologies with measurable outcomes.
On the platform engineering side, you will architect cloud-native services and APIs, design service decomposition and event-driven flows, and treat multi-tenancy as a first-class concern with isolation models, noisy-neighbor controls, and cost attribution. You will lead platform modernization initiatives—monolith decomposition, migrations, and deprecations—through to completion.
Reliability and operations are critical: you will drive platform reliability, availability, and performance optimization; own complex production issues in distributed SaaS environments; and define SLOs, failure modes, and capacity planning. You will write clean, maintainable, high-performance production code, establish rigorous engineering standards through code reviews and CI/CD, and identify and drive practical refactoring of architectural bottlenecks and technical debt.
You will provide architectural guidance across multiple teams, lead architecture reviews and design discussions, mentor senior and staff engineers through reference implementations and sponsorship, and articulate complex trade-offs to both technical and executive stakeholders. Security, privacy, and compliance are embedded: you will ensure designs align with information security standards and regulatory requirements, with emphasis on tenant isolation, access control, auditability, and data residency.
The ideal candidate combines deep technical expertise in distributed systems, multi-tenant SaaS architecture, microservices, and event-driven design with strong leadership and stakeholder management capabilities—and remains genuinely hands-on, writing production code and leading deep debugging when it matters.
**Requirements:**
- Bachelor's or Master's degree in Computer Science, Engineering, Information Systems, or related discipline (or equivalent practical experience)
- 14+ years of software engineering, platform engineering, or systems architecture experience in modern distributed SaaS environments
- Expert-level backend engineering in Java, Python, Go, or equivalent—currently hands-on
- Proven experience designing and operating enterprise-scale, multi-tenant SaaS platforms with real numbers for throughput, latency, availability, and behavior under failure
- Strong understanding of distributed systems fundamentals: consistency and idempotency, retries and backpressure, concurrency, caching, and database design and optimization
- Demonstrated ownership of large-scale migrations or modernization initiatives with measurable outcomes
- Advanced production debugging skills—Linux internals, profiling, log analysis, and telemetry in distributed cloud environments
- Experience leading cross-functional architecture initiatives in SaaS or product organizations
**Good to Have:**
- Data platform and analytics experience: batch and real-time data ingestion, transformation, and serving architectures; streaming and CDC (Kafka, Kinesis, Debezium); lakehouse and modern data platform technologies (Delta Lake, Iceberg, Databricks, Snowflake)
- Data governance practice: metadata management, cataloging, lineage, and data quality frameworks
- Feature and training data architectures supporting AI/ML initiatives
- ClickHouse, OpenSearch, or similar analytical and search engines
- AI-native product capabilities: RAG, agentic workflows, and LLM integration in production
- FinOps practice: cost attribution, showback, and efficiency guardrails at platform scale
