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Freshworks

Principal Engineer - Systems

Freshworks is hiring a Principal Engineer - Systems in Hyderabad, India. Level rates it ; you can apply on Freshworks.

Level's read on this job

  • On Level's scale, this role is Little AI ●○○○: aI is not part of the work.
  • The posting mentions Databricks, Microservices and API among its tools and skills.
  • Level classes it as a senior role.
  • Freshworks has 122 other open roles on Level.

AI in this role

Design and evolve enterprise-scale platform architecture for multi-tier SaaS products at Freshworks.

DatabricksMicroservicesAPI
ragllm-integrationai-agentsdistributed-systemssaasarchitectureplatform-engineering

About Freshworks:

Organizations everywhere struggle under the crushing costs and complexities of “solutions” that promise to simplify their lives. To create a better experience for their customers and employees. To help them grow. Software is a choice that can make or break a business. Create better or worse experiences. Propel or throttle growth. Business software has become a blocker instead of ways to get work done.

There’s another option. Freshworks. With a fresh vision for how the world works.

Freshworks Inc. builds uncomplicated service software that delivers exceptional employee and customer experiences. Our people-first approach to AI eliminates friction, helping businesses reduce complexity, lower cost-to-serve, and deliver faster, more human support through enterprise-grade yet easy-to-use CX and IT solutions. Nearly 75,000 companies, including Bridgestone, New Balance, Nucor, S&P Global, and Sony Music, trust Freshworks to power their Employee Experience (EX) and Customer Experience (CX) operations.

Fresh vision. Real impact. Come build it with us.

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.

At Freshworks, we have fostered an environment that enables everyone to find their true potential, purpose, and passion, welcoming colleagues of all backgrounds, genders, sexual orientations, religions, and ethnicities. We are committed to providing equal opportunity and believe that diversity in the workplace creates a more vibrant, richer environment that boosts the goals of our employees, communities, and business. Fresh vision. Real impact. Come build it with us.

How we rate this

Principal Engineer - Systems at Freshworks rates 10 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.

Classification

Little AI. AI is not part of the work.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

RAGLLM IntegrationAI agentsDistributed SystemsSaasArchitecturePlatform EngineeringDatabricks

Questions you could be asked

  1. How would you design a retrieval step so the model answers from real data instead of guessing?
  2. How have you integrated a large language model into a production application?
  3. How do you decide when an AI agent can act on its own versus asking for approval first?
  4. Tell me about a project where distributed systems was part of your work. What did you do?
  5. Tell me about a project where saas was part of your work. What did you do?

Adapt your resume

  • List these exact terms on your resume: RAG, LLM Integration, AI agents, Distributed Systems, and Saas. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.

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