We use analytics and advertising cookies to understand how the site is used and whether our ads on Facebook and Instagram work. They are set only if you accept. See our Privacy Policy for details.
Prep for the AWS Solutions Architect loop: technical breadth and depth, a customer-facing architecture presentation or whiteboard, and Leadership Principles in every round.
AWS Solutions Architects are customer-facing technical advisors: they help customers design, migrate and operate workloads on AWS. The interview reflects that mix. Expect a phone screen, then a loop of roughly four to six interviews in which nearly every interviewer asks Leadership Principle questions alongside their technical area. Technical rounds test breadth across core AWS services and depth in one area (for example networking, databases, analytics, security, or machine learning for specialist roles), usually through an architecture whiteboard on a customer scenario rather than coding. Many loops also include a presentation, in which you walk a panel through an architecture you have built or a prepared customer scenario and handle questions as if they were the customer. One interviewer is a Bar Raiser - a trained interviewer from outside the hiring team whose job is to keep the hiring bar consistent across Amazon. The exact set of rounds varies by team, level and specialty, so confirm the shape of your loop with your recruiter.
Every technical round. Know the core services well enough to explain how they work and when not to use them: EC2, S3, VPC, IAM, RDS and Aurora, DynamoDB, Lambda, ELB, CloudFront, SQS and SNS, CloudWatch.
The whiteboard and presentation. Practice end-to-end designs - multi-AZ web apps, migrations, event-driven systems, data lakes - and justify them against the Well-Architected Framework's six pillars.
Leadership Principles appear in almost every round. Prepare 10-12 STAR stories with measurable results, especially customer obsession, earn trust, dive deep, ownership, deliver results and learn and be curious.
A common depth area and a common weak spot: VPC design, subnets and routing, security groups vs NACLs, hybrid connectivity (VPN, Direct Connect), DNS with Route 53, and load balancing.
IAM policies and least privilege, encryption at rest and in transit, KMS, shared responsibility, and how you would secure a multi-account environment.
Choosing between relational and NoSQL for a customer workload, replication and read scaling, backups and disaster recovery, and migration approaches.
General distributed-systems reasoning - caching, queues, consistency, scaling - underpins the cloud designs even when the conversation is framed in AWS services.
Increasingly relevant for generative AI and machine learning specialist SA roles: Bedrock, retrieval-augmented generation, and how to evaluate and cost an AI workload for a customer.
Curated walkthroughs for the bounded designs that show up in Amazon's system design rounds. Capacity estimation, architecture, deep-dives, and trade-offs.
The front door to a microservice fleet. One layer that every external request crosses - so it owns auth, rate limiting, routing, and resilience, and absolutely cannot become the bottleneck.
Edge cache hierarchies, cache key design, invalidation, origin shield, and edge compute - the system every other system relies on without thinking about it.
Namespace vs bytes, erasure coding vs replication, the eleven-nines durability math, multipart upload, and why LIST is the hardest API in the system.
Partitions, consumer groups, replication, retention, and the exactly-once myth - the implementation details Kafka users gloss over until they don't.
Consistent hashing, eviction, replication, and what really happens when a single hot key takes down the cluster.
Batch vs streaming, lambda vs kappa, the warehouse-vs-lakehouse decision, and dimension modeling that survives schema drift.
Sample STAR answers, common prompts, pitfalls, and follow-up strategies for the behavioral themes that decide Amazon's loop.
The most-asked Amazon LP. Interviewers screen for evidence you reasoned about end-user impact, not just shipped a feature.
Amazon's bar for how leaders build credibility: listen, speak candidly, treat others respectfully, and be vocally self-critical even when it is awkward.
Leaders operate at all levels. The interviewer is testing whether you actually understand your own systems - or whether you summarize what your team built.
Tested at every level, scored harder at senior. Did you take responsibility for outcomes - or just for tasks?
Amazon's outcome bar: focus on the key inputs, deliver them with the right quality and on time, and rise to the occasion when things get hard - never settle.
Interviewers want self-driven learning that produced a concrete result - not a list of courses you took or technologies you've 'heard of.'
This LP is a trap if you read it as 'I'm always right.' Interviewers screen for strong judgment under uncertainty AND willingness to be disconfirmed.
The solutions architect learning path and the judgment cases that mirror this loop's execution and metrics questions.
Total comp ranges, base, equity, and bonus across the levels tested in this loop. Aggregated from public sources.
0 Solutions architect levels covered. Updated 2026-05.
653 MCQs and 27 coding challenges, grouped by topic. Free preview shows question titles - premium unlocks full content.
Behavioral and system design rounds reward practice with a live AI interviewer that probes follow-ups, not silent reading.
Start an AI mock interview →Generally not in the form of algorithm problems. The technical rounds focus on architecture, AWS services and customer scenarios. Some specialist roles may ask you to read or reason about code, scripts or infrastructure as code, so ask your recruiter if your role has a coding component.
Many SA loops ask you to prepare a short technical presentation - commonly an architecture you designed or a customer scenario given in advance - and then present it to a panel who ask questions as a customer would. It tests your technical judgment and how you communicate with a customer at the same time. Formats differ by team, so confirm the length, topic and audience with your recruiter.
Very. Almost every interviewer in the loop is assigned Leadership Principles to assess, alongside any technical area. Prepare specific STAR stories with real numbers, and expect follow-up questions that dig into what you personally did. Customer obsession and earning trust are especially relevant for a customer-facing role.
The Bar Raiser is a trained interviewer from outside the hiring team who takes part in the loop to keep hiring standards consistent across Amazon. They usually focus on Leadership Principles and take part in the debrief. You will not always know which interviewer it is, so treat every round as if it counts equally.
Certifications are not a substitute for the interview, but they are a structured way to build the breadth the loop expects, and the Solutions Architect Associate and Professional exams map closely to the technical breadth round. Real experience designing and running systems matters more than the certificate itself.