Interview experience
Freshworks Interview Questions and Answers (2026)
Overview
Section titled “Overview”Freshworks runs a compact 4-stage loop, but it leans closer to a product-company bar than a typical services-firm interview - medium-to-hard DSA, a real system-design round, and SaaS-specific scenario questions.
Freshworks interview process at a glance
Section titled “Freshworks interview process at a glance”| Round | Duration | What they test |
|---|---|---|
| Online Assessment | 90-120 min | 2-3 coding problems (DSA) |
| Technical Round 1 | 45-60 min | DSA + detailed project discussion |
| Technical Round 2 | 45-60 min | DSA / system design basics |
| Hiring Manager / HR | 30-45 min | Behavioural + team fit |
Online Assessment
Section titled “Online Assessment”A timed coding test with 2-3 DSA problems that run medium to hard rather than easy warm-ups - candidates report questions spanning array manipulation, tree traversal, and dynamic programming, usually on a proctored platform like HackerRank.
Common questions
- Array manipulation problems requiring an optimal (not brute-force) solution
- Tree traversal problems (level order, path-sum variants)
- A dynamic-programming problem under time pressure
- Edge-case handling is scored, not just the happy path
Technical Round 1
Section titled “Technical Round 1”A DSA round paired with a detailed walkthrough of your strongest project - interviewers expect you to justify data-structure choices and explain time/space complexity out loud, not just arrive at a working answer.
Common questions
- Find the longest increasing subsequence in an array
- Design a data structure for an LRU cache (HashMap + doubly linked list)
- Explain the time and space complexity of your solution
- Walk through the architecture and hardest bug in your most complex project
Technical Round 2
Section titled “Technical Round 2”DSA continues, but this round is where Freshworks’ SaaS product angle shows up most - expect a lightweight system-design prompt scoped to what a strong fresher can reason through, not enterprise-scale distributed systems.
Common questions
- Design a customer support ticketing system
- How would you design REST APIs for a SaaS product?
- Discuss database schema design and a caching strategy (e.g. Redis) for it
- Trade-offs between scalability, availability, and consistency for the scenario given
Hiring Manager / HR
Section titled “Hiring Manager / HR”A closing 30-45 minute conversation blending a managerial-style discussion (problem-solving, ambiguity, “why Freshworks”) with standard HR topics - compensation, joining date, relocation, and benefits.
Common questions
- Describe a time you solved a complex technical problem
- How do you handle conflicting priorities?
- Why Freshworks, and why a SaaS product company over a services firm?
- Tell me about a time you took ownership of a feature or problem beyond your assigned scope
Sample answer frameworks for each of these are on the Freshworks HR interview questions page.
Freshworks is a SaaS product company, not a staffing firm
Section titled “Freshworks is a SaaS product company, not a staffing firm”Unlike most large Indian IT employers, Freshworks builds and sells its own SaaS products (Freshdesk, Freshsales, Freshservice, Freshchat) rather than staffing engineers onto client projects. That shapes the interview in two ways: system-design prompts are framed around Freshworks’ own product domains (support ticketing, CRM workflows, multi-tenant SaaS architecture), and the HR round explicitly probes why you want a product company over a services firm - a generic “good brand name” answer lands worse than one tied to Freshworks’ actual products.
Common technical interview questions and answers
Section titled “Common technical interview questions and answers”Q: How do you design an LRU cache with O(1) get and put?
Combine a hash map with a doubly linked list. The hash map stores key to node pointer for O(1) lookup, and the doubly linked list keeps entries in recency order with the most recently used at the head and the least recently used at the tail. On get, find the node through the map and move it to the head. On put, insert at the head, and if capacity is exceeded, evict the tail node and remove its key from the map. A doubly linked list is essential because unlinking a node in O(1) needs its previous pointer, which a singly linked list does not have. Sentinel head and tail nodes eliminate most null checks, and Java’s LinkedHashMap with accessOrder set to true is the built-in equivalent.
Q: How do you find the longest increasing subsequence in an array?
The classic dynamic-programming solution defines dp[i] as the length of the longest increasing subsequence ending at index i, computed by scanning every earlier index j whose value is smaller and taking the best dp[j] plus one; the answer is the maximum over all dp entries, at O(n^2) time and O(n) space. The optimal solution is O(n log n): maintain an array tails where tails[k] holds the smallest possible tail value of an increasing subsequence of length k plus one, and for each element binary-search for the first tail greater than or equal to it, replacing it, or appending when none exists. The length of tails is the answer - but tails itself is not a valid subsequence, so reconstructing the actual sequence requires storing predecessor indices.
Q: How would you design a customer support ticketing system?
Start with entities: tickets, customers, agents, teams, comments, attachments and SLA policies, with a ticket carrying status, priority, requester, assignee and timestamps. The core flows are ticket creation from multiple channels such as email, web form and chat, routing to an agent by round robin or skill-based rules, and status transitions modelled as an explicit state machine. Reads dominate writes, so index on assignee and status for agent queues, use a search engine such as Elasticsearch for full-text ticket search rather than a LIKE query, and cache agent dashboards. SLA breach detection is best handled by a scheduled job or delayed queue message rather than polling every ticket, and notifications and attachment processing go through an async queue so ticket creation stays fast.
Q: What is multi-tenant architecture, and what are the isolation options?
Multi-tenancy means one application instance serves many customer organisations while keeping their data separate. There are three common models. A separate database per tenant gives the strongest isolation and easiest per-tenant backup or restore, but costs the most and makes schema migrations across thousands of tenants painful. A shared database with a schema per tenant is the middle ground. A shared schema with a tenant_id column on every table is cheapest and most scalable and is what most SaaS products use, but every query must filter by tenant_id - one missing filter is a cross-customer data leak, which is why it is enforced at the ORM or row-level-security layer rather than left to individual queries. Large tenants are often moved onto dedicated infrastructure so one noisy customer cannot degrade the rest.
Q: What makes a REST API well designed?
Model resources as nouns and let HTTP methods carry the verbs, so GET /tickets/123 and POST /tickets rather than GET /getTicket. Respect the semantics: GET is safe and cacheable, PUT is idempotent and replaces the whole resource, PATCH updates part of it, and DELETE is idempotent even though a second call returns 404. Use real status codes - 201 with a Location header on creation, 400 for a malformed request, 401 versus 403 for unauthenticated versus unauthorised, 409 for a conflict, 429 for rate limiting. Version the API in the path or a header so it can evolve without breaking clients, paginate every collection with cursor-based paging rather than offsets on large tables, and return structured error bodies with a stable machine-readable code.
Q: When would you add a cache, and what invalidation strategy would you use?
Cache when a read is expensive and repeated and the data tolerates being slightly stale - agent dashboards, ticket-count aggregates and configuration all qualify, whereas the authoritative ticket record during an edit does not. Cache-aside is the usual pattern: the application checks Redis, falls back to the database on a miss, and writes the result back with a TTL. Write-through keeps the cache consistent at the cost of write latency, while write-behind is fastest but risks losing data on a crash. Invalidation is the hard part: a TTL is the simplest safety net, explicit invalidation on write is more accurate but easy to miss on some code path, and versioned cache keys sidestep deletion entirely. Also plan for stampedes, where one hot key expiring sends every request to the database at once - use a lock or probabilistic early refresh.
Q: How do you do a level-order traversal of a binary tree, and how does it differ from DFS traversals?
Level-order is BFS: push the root into a queue, then repeatedly pop a node, record it, and push its children. To emit one list per level, record the queue size at the start of each iteration and process exactly that many nodes. It runs in O(n) time with O(w) space, where w is the maximum width of the tree - for a complete tree about n/2, so BFS can use more memory than DFS on wide trees. Preorder, inorder and postorder are DFS variants distinguished by when the node is visited relative to its children, use O(h) stack space, and inorder on a binary search tree yields sorted output. Choose BFS for shortest paths and level-based questions, DFS for structural recursion like depth, diameter or subtree checks.
Q: What is the difference between an abstract class and an interface?
An abstract class can hold state - instance fields, constructors and fully implemented methods - and expresses an is-a relationship with shared implementation, but a class may extend only one. An interface declares a contract; since Java 8 it can carry default and static methods, and since Java 9 private helper methods, but it still cannot hold instance state, and a class may implement many. The practical rule is to use an abstract class when subclasses genuinely share code and fields, and an interface when unrelated classes need to expose the same capability. Prefer interfaces at dependency boundaries because they keep coupling loose and make test doubles trivial; when two interfaces supply colliding default methods, the implementing class must resolve the conflict explicitly.
Frequently asked questions about Freshworks interviews
Section titled “Frequently asked questions about Freshworks interviews”What is the Freshworks interview process for freshers?
Freshworks interview process for SDE / Software Engineer typically includes: 1. Online Assessment (90-120 min): 2-3 coding problems (DSA), medium to hard difficulty. 2. Technical Round 1 (45-60 min): DSA plus a detailed project discussion. 3. Technical Round 2 (45-60 min): DSA and system design basics, often a SaaS-flavoured scenario like a ticketing system or multi-tenant API. 4. Hiring Manager / HR (30-45 min): Behavioural, team fit, and offer discussion. Timeline is usually 2-4 weeks from application to offer for campus drives.
What questions are asked in Freshworks interviews?
Freshworks interviews commonly cover medium-to-hard DSA (arrays, trees, dynamic programming, LRU cache design), core CS (OOPs, SQL), a deep project walkthrough, and SaaS-specific system design - multi-tenant architecture, REST API design, and CRM/support-ticketing workflows. Behavioural rounds check ownership, teamwork, and why Freshworks over a services company.
How many rounds are there in the Freshworks interview?
Freshworks typically has 4 stages: Online Assessment (90-120 min), Technical Round 1 (45-60 min), Technical Round 2 (45-60 min), Hiring Manager / HR (30-45 min). Some drives split the managerial and HR conversations into two separate short rounds instead of one. Check that cycle’s college placement email for the exact count.
Does Freshworks ask system design questions to freshers?
Yes, in Technical Round 2. It’s not full-blown distributed-systems design - expect SaaS-shaped prompts like designing a customer support ticketing system or REST APIs for a SaaS product, with follow-ups on database schema, caching, and scalability trade-offs at a level a strong fresher can reason through out loud.
How should I prepare for Freshworks interviews?
Practise timed medium-to-hard DSA (not just easy problems), revise OOPs and SQL, prepare one crisp project narrative you can defend in depth, and read up on SaaS multi-tenant architecture and REST API design since Freshworks builds and sells its own SaaS products rather than staffing client projects. Use STAR for behavioural answers.
Is Freshworks’ interview harder than a typical IT-services company interview?
Generally yes. Freshworks is a product company (Freshdesk, Freshsales, Freshservice) rather than a staffing/services firm, so its bar leans closer to a product-company loop: harder DSA, a real system-design round, and interviewers who probe project depth and design trade-offs rather than just checking syntax knowledge.