Principal Engineer - Systems

Role Overview
We are seeking a highly experienced Principal Engineer to lead the design and evolution of the enterprise-scale platform architecture that powers Freshworks’ multi-tier SaaS products. This role will define the architecture strategy for a major platform domain, drive modernization initiatives, and establish best practices across service design, reliability, engineering quality, and cost.
The ideal candidate combines deep technical expertise in distributed systems, multi-tenant SaaS architecture, microservices, event-driven design, and large-scale production operations with strong leadership and stakeholder management capabilities — and remains genuinely hands-on, writing production code and leading deep debugging when it matters.
Key Responsibilities
Architecture & Strategy
Define and own the platform architecture roadmap for your domain, including the target state and a realistic path to it.
Design scalable, secure, and cost-efficient architectures supporting high-throughput, low-latency, multi-tenant workloads.
Establish architecture standards, design principles, decision records, and review practices.
Evaluate emerging technologies and own build-versus-buy decisions with measurable outcomes.
Platform Engineering
Architect and build cloud-native services and APIs that scale with global growth.
Design service decomposition, API contracts, messaging and event-driven flows, caching strategies, and database-layer design.
Treat multi-tenancy as a first-class design concern: isolation models, noisy-neighbour control, per-tenant limits, and cost attribution.
Lead platform modernization — monolith decomposition, migrations, and deprecations carried through to completion.
Reliability, Performance & Operations
Drive platform reliability, availability, performance optimization, and observability.
Take ownership of complex production issues in distributed SaaS environments, leading deep root-cause analysis and implementing permanent preventive safeguards.
Define SLOs, failure modes, resilience patterns, and capacity planning for the systems you own.
Engineering Excellence & Quality
Write clean, maintainable, high-performance production code and build proof-of-concepts that settle architectural questions.
Establish rigorous engineering standards through code reviews, automated testing, and CI/CD integration.
Identify architectural bottlenecks and technical debt, and drive practical, iterative refactoring without compromising business delivery.
Security, Privacy & Compliance
Ensure platform designs and team practices align with information security standards and regulatory requirements.
Design for tenant isolation, access control, auditability, and data residency from the outset.
Technical Leadership
Provide architectural guidance across multiple engineering teams.
Lead architecture reviews, design discussions, and technical decision-making.
Mentor senior and staff engineers, raising the bar through reference implementations and sponsorship rather than authority.
Influence engineering strategy and long-term technology investments; articulate complex trade-offs to both technical panels and executive stakeholders.
Required Qualifications
Bachelor’s or Master’s degree in Computer Science, Engineering, Information Systems, or a related discipline — or equivalent practical experience.
14+ years of experience in software engineering, platform engineering, or systems architecture within 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 behaviour 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 & Analytics
Batch and real-time data ingestion, transformation, and serving architectures; streaming and CDC (Kafka, Kinesis, Debezium).
Lakehouse and modern data platform technologies such as Delta Lake, Iceberg, Databricks, Snowflake, and cloud-native data services.
Reusable data models, semantic layers, and curated data products enabling self-service analytics.
Data governance practice — metadata management, cataloging, lineage, and data quality frameworks.
Feature and training data architectures supporting AI/ML initiatives.
Adjacent Experience
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.

Employment type
Full-time

Work arrangement
Hybrid