Amazon Recruitment Process for Freshers: SDE and CSA Guide 2026

Amazon’s India campus hiring runs two distinct tracks: Software Development Engineer and Cloud Support Associate, each with a written test, three technical rounds, and an HR interview.

The structure is the same for both roles. The difference is in what each track measures: SDE interviews go deep on algorithms and data structures, while CSA interviews split attention across coding, operating systems, networking, and DBMS. This guide covers what each stage looks like in 2026 and what to focus on in prep.

Amazon Development Centre India operates out of Bangalore, Hyderabad, and Chennai. Campus drives run both on-campus and through off-campus pools on Amazon’s India careers portal; eligibility criteria and test format are the same either way.

How Amazon Structures Its Campus Hiring

Both SDE and CSA roles follow a five-stage sequence. The stages are identical; the content of each stage differs.

Stage	SDE	CSA
Written Test	20 MCQs + 2 coding problems, 90 min, negative marking	25 aptitude + 40 technical MCQs + 2 coding problems, 120 min, no negative marking
Technical Round 1	DSA-focused coding interview	OS, Networking, DBMS, DSA mix
Technical Round 2	DSA-focused coding interview	OS, Networking, DBMS, DSA mix
Technical Round 3	DSA-focused coding interview	OS, Networking, DBMS, DSA mix
HR Interview	Leadership Principles behavioral	Leadership Principles behavioral (longer)

The SDE track is for candidates targeting software development. The CSA track is for cloud support roles, where day-to-day work involves troubleshooting AWS infrastructure, managing support escalations, and working with networking and OS-level diagnostics. The two tracks require overlapping but distinct prep strategies.

What the Online Assessment Covers

SDE Online Assessment

The SDE written test covers:

• 20 MCQs across aptitude, logical reasoning, and technical topics (Time Complexity, C language, DBMS)
• 2 programming problems: one algorithm-based, one mathematical
• 90 minutes total
• Negative marking applies to the MCQ section

The negative marking rule changes the optimal strategy. Skipping a question you are 50-50 on is often better than guessing. Accuracy matters more than coverage in the MCQ section. For the coding problems, write working code with comments and correct complexity; partial solutions are evaluated lower than clean, complete ones even if the logic is sound.

CSA Online Assessment

The CSA test covers:

• 25 aptitude questions
• 40 technical MCQs covering OS, DBMS, DSA, and Networking
• 2 coding problems
• 120 minutes total
• No negative marking

No negative marking means covering the entire paper is the right approach. The technical MCQ block is where most CSA candidates underperform. Students from ECE and EEE branches who haven’t revisited OS and Networking topics since third semester often find the 40 technical questions harder than the aptitude section. Plan for that gap.

Three Technical Interview Rounds

Both tracks put candidates through three successive technical interview rounds. Each round is conducted by a full-time Amazon engineer, not an HR team member.

SDE Technical Rounds

All three rounds focus on data structures and algorithms. The interview format is conversational: the interviewer states a problem, you ask clarifying questions, talk through your approach, and write code in a shared editor or on a whiteboard.

Sample problems from past SDE interview pools:

• Modify a linked list 1–2–3–4–5–6–7–8 to produce 1–3–5–7–8–6–4–2
• Rearrange a linked list so odd-indexed nodes come first, then even-indexed, in O(n) time
• Given an array of time ranges, merge all overlapping intervals and return the result

Interviewers expect time and space complexity analysis for every solution. A correct answer with no complexity discussion lands lower than a correct answer with a clear O(n) or O(n log n) explanation. Code quality matters too: proper variable names, comments on non-obvious steps, and clean logic all factor in.

See the data structures reference guide for the topic coverage that maps most closely to what Amazon’s SDE rounds test.

CSA Technical Rounds

CSA technical rounds cover a wider surface area:

• Operating Systems: paging concepts (page directories, page-directory pointers, PAE), process scheduling, memory management, priority queues
• Networking: TCP three-way handshake, DNS resolution, ARP, troubleshooting scenario-based questions (for example: “DNS and ARP stopped working. Walk me through how you’d diagnose this”)
• DBMS: SQL joins, normalisation, indexing, transactions
• DSA: sorting algorithms (Quick Sort and its optimisation strategies come up frequently), binary trees, general problem-solving

A question type that appears often in CSA rounds: “Walk me through what happens when you type a URL in a browser.” That single question covers DNS, TCP/IP, HTTP, and OS process scheduling. Interviewers use it to probe depth across the entire CS fundamentals stack in one thread.

CSA technical rounds are lighter on pure DSA than SDE, but the breadth requirement means candidates who haven’t touched OS or Networking since Year 2 get caught out in Round 1.

The HR Round: Leadership Principles in Practice

Amazon’s 16 Leadership Principles are not a list of corporate values to memorise. They are operational guidelines Amazon engineers actually use in day-to-day decision-making. The HR round tests whether you can produce specific, real examples that reflect those principles.

The principles tested most in campus drives:

• Customer Obsession: start from what the end user needs, not from what is technically convenient
• Ownership: take responsibility beyond your assigned scope; fix the thing you didn’t cause if it blocks the team
• Bias for Action: ship something imperfect over waiting for perfect when the cost of delay is higher than the cost of a mistake
• Deliver Results: meet commitments under real constraints, not idealised ones
• Dive Deep: engage with the actual data and detail, not the summary

Prepare one clear STAR-format story (Situation, Task, Action, Result) for each of these five principles. The stories should come from real academic projects, internships, hackathons, or campus leadership roles. Generic answers that name a principle without a specific project, a specific constraint, or a measurable outcome land poorly.

The CSA HR round is harder than the SDE one. CSA roles involve direct client interaction, so interviewers probe interpersonal judgment, stress responses, and communication clarity more actively than in the SDE track.

A Practical Prep Approach

For SDE Candidates

• DSA first: linked lists, binary trees, dynamic programming, graph traversal, sorting algorithms. Aim for problem-level fluency, not pattern memorisation.
• Complexity analysis for every problem: state time and space complexity before moving to the next problem, not after.
• Practice in a plain editor: interviews use a basic shared editor with no autocomplete. Practicing in an IDE with IntelliSense creates muscle-memory that doesn’t transfer.
• Leadership Principles prep: even the SDE HR round tests these. Prepare five stories and keep them under two minutes each.

For CSA Candidates

• Split time 40/40/20: 40% DSA, 40% OS/Networking/DBMS, 20% Leadership Principles stories.
• OS and Networking coverage: work through a concise OS textbook for paging, scheduling, and file systems; cover IP addressing, TCP/UDP, and subnetting fundamentals. The “URL in a browser” question type rewards depth across all of these, not surface knowledge of any one.
• DBMS: SQL joins, normalisation to 3NF, index types (B-tree vs hash), and transaction isolation levels.
• LP stories: the CSA HR round is longer and the questions more probing. Five stories won’t be enough; prepare eight and rehearse them until they’re fluent rather than recited.

For a comparison of how a similar product-company hiring process runs, MAQ Software’s recruitment process covers a comparable multi-round DSA-heavy format and is a useful benchmark for the effort level these technical rounds require.

Amazon’s SDE technical rounds specifically reward candidates who can decompose a problem, state trade-offs between approaches, and improve an initial solution under time pressure. That same discipline of iterative refinement and complexity awareness is what ML engineers use when evaluating model architectures and building evaluation pipelines. If you want to test whether that mental model transfers to applied AI work, TinkerLLM at ₹299 is the entry point: a real LLM environment where the same problem-solving habits from interview prep connect to shipping something.