AI Screenr
AI Interview for Solutions Architects

AI Interview for Solutions Architects — Automate Screening & Hiring

Automate screening for solutions architects with AI interviews. Evaluate enterprise architecture patterns, cloud platform knowledge, and API strategy — get scored hiring recommendations in minutes.

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By AI Screenr Team·

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The Challenge of Screening Solutions Architects

Hiring solutions architects demands deep dives into enterprise architecture patterns, cloud platform expertise, and integration strategies. Your team is burdened with repetitive interviews and discovery sessions, only to uncover that many candidates can’t articulate beyond generic cloud knowledge or struggle with stakeholder communication. Surface-level responses often gloss over critical trade-offs and compliance considerations, leading to misalignment in technical expectations.

AI interviews streamline the process by conducting thorough assessments on technical discovery skills, reference architecture patterns, and trade-off reasoning. The AI delves into the nuances of cloud platforms and integration strategies, generating detailed evaluations. This enables you to replace screening calls and efficiently identify candidates who excel in both technical depth and stakeholder engagement, saving valuable engineering resources for later interview stages.

What to Look for When Screening Solutions Architects

Designing scalable enterprise architectures using AWS, Azure, or GCP services
Conducting thorough technical discovery sessions with enterprise clients
Defining API strategy with REST, GraphQL, and gRPC
Evaluating cost and compliance trade-offs in cloud environments
Crafting integration strategies using Kubernetes and Kafka for distributed systems
Presenting complex solutions through effective whiteboard sessions and proposals
Leveraging Kubernetes for container orchestration and management
Developing reference architectures for cloud-native applications
Facilitating stakeholder communication to align technical and business goals
Balancing performance and cost in cloud infrastructure design

Automate Solutions Architects Screening with AI Interviews

AI Screenr evaluates solutions architects by probing enterprise architecture patterns, cloud strategies, and integration techniques. Weak answers trigger deeper exploration. Discover more about our automated candidate screening process.

Architecture Pattern Analysis

Examines understanding of enterprise patterns, including microservices and event-driven architectures, with adaptive follow-up questions.

Cloud Strategy Evaluation

Assesses depth in AWS, Azure, and GCP, pushing candidates on platform-specific strengths and weaknesses.

Integration Insight Scoring

Scores API strategy and integration answers, probing further into REST, GraphQL, and gRPC knowledge.

Three steps to your perfect solutions architect

Get started in just three simple steps — no setup or training required.

1

Post a Job & Define Criteria

Create your solutions architect job post with required skills like enterprise architecture patterns, cloud platform expertise, and integration strategy. Or paste your job description and let AI generate the screening setup automatically.

2

Share the Interview Link

Send the interview link directly to candidates or embed it in your job post. Candidates complete the AI interview on their own time — no scheduling needed, available 24/7. For more details, see how it works.

3

Review Scores & Pick Top Candidates

Get detailed scoring reports for every candidate with dimension scores, evidence from the transcript, and clear hiring recommendations. Shortlist the top performers for your second round. Learn more about how scoring works.

Ready to find your perfect solutions architect?

Post a Job to Hire Solutions Architects

How AI Screening Filters the Best Solutions Architects

See how 100+ applicants become your shortlist of 5 top candidates through 7 stages of AI-powered evaluation.

Knockout Criteria

Automatic disqualification for deal-breakers: minimum years of enterprise architecture experience, cloud certification, work authorization. Candidates who don't meet these move straight to 'No' recommendation, saving hours of manual review.

82/100 candidates remaining

Must-Have Competencies

Each candidate's ability to design AWS reference architectures, handle integration challenges, and communicate technical proposals is assessed and scored pass/fail with evidence from the interview.

Language Assessment (CEFR)

The AI evaluates the candidate's ability to articulate complex architecture decisions at the required CEFR level (e.g. B2 or C1), crucial for roles involving stakeholder presentations.

Custom Interview Questions

Your team's most critical questions on cloud platform strategies and API integration are asked consistently. The AI probes deeper into vague answers to uncover real-world implementation experience.

Blueprint Deep-Dive Questions

Pre-configured technical questions like 'Explain the trade-offs in using Kubernetes vs serverless architectures' with structured follow-ups. Ensures every candidate receives equal evaluation depth.

Required + Preferred Skills

Each required skill (enterprise architecture patterns, cloud platforms) is scored 0-10 with evidence snippets. Preferred skills (Kafka, GraphQL) earn bonus credit when demonstrated.

Final Score & Recommendation

Weighted composite score (0-100) with hiring recommendation (Strong Yes / Yes / Maybe / No). Top 5 candidates emerge as your shortlist — ready for technical interview.

Knockout Criteria82
-18% dropped at this stage
Must-Have Competencies65
Language Assessment (CEFR)50
Custom Interview Questions36
Blueprint Deep-Dive Questions24
Required + Preferred Skills14
Final Score & Recommendation5
Stage 1 of 782 / 100

AI Interview Questions for Solutions Architects: What to Ask & Expected Answers

When interviewing solutions architects — whether manually or with AI Screenr — it's crucial to focus on the candidate's ability to design scalable, cost-effective solutions while effectively communicating with stakeholders. The questions below are crafted based on industry standards and insights from AWS Well-Architected Framework to assess core competencies in cloud architectures and enterprise integration strategies.

1. Technical Discovery Skills

Q: "How do you approach technical discovery during project initiation?"

Expected answer: "In my previous role, I led technical discovery for a healthcare SaaS platform. We started with stakeholder workshops to gather requirements and constraints. I used tools like Lucidchart for visualizing workflow and dependencies. This approach helped identify critical integrations with HL7 interfaces early on. By involving our DevOps team, we aligned on AWS services like Lambda for event-driven architectures, reducing our time-to-market by 30%. The key is maintaining open channels with all stakeholders — this ensures no critical requirement is overlooked."

Red flag: Candidate struggles to explain the importance of stakeholder engagement or relies solely on technical details without considering business context.


Q: "What tools do you use for gathering technical requirements?"

Expected answer: "At my last company, we leveraged Jira and Confluence extensively for managing technical requirements. Jira helped us track project tasks and issues, while Confluence was our go-to for documentation and collaborative editing. For real-time collaboration, Miro was invaluable, especially during remote sessions. This toolkit allowed us to reduce requirement misalignment by 25%, as confirmed in our post-mortem analysis. The seamless integration between these tools also facilitated smoother handoffs between teams, particularly during the design phase."

Red flag: Candidate cannot name specific tools or gives vague answers like "we just talked to people."


Q: "Describe a challenging technical discovery situation and how you resolved it."

Expected answer: "In a recent project, we faced a tight deadline for a fintech client requiring integration with legacy systems. Initial discovery revealed undocumented APIs. I organized a rapid discovery sprint using Swagger to auto-generate API documentation. This allowed us to map dependencies and identify bottlenecks. By the end of the sprint, we had a clear path forward, cutting integration time by 40%. My approach was data-driven, leveraging metrics from Swagger to ensure accurate API mapping and documentation."

Red flag: Candidate cannot provide a concrete example or focuses only on problems without discussing solutions.


2. Reference Architecture Patterns

Q: "Can you provide an example of a reference architecture you designed?"

Expected answer: "In my role at a logistics tech firm, I designed a microservices-based architecture using AWS Fargate for containerized deployments. We adopted a serverless approach with AWS Lambda for certain event-driven processes. This architecture reduced our infrastructure costs by 20% and improved deployment cycles by 50%. We also implemented Amazon RDS for scalable database management, which supported real-time analytics with minimal latency. Our architecture became a blueprint for subsequent projects, streamlining our development efforts significantly."

Red flag: Candidate lacks experience with designing architectures or mentions outdated patterns without rationale.


Q: "How do you ensure your architecture is scalable and secure?"

Expected answer: "Scalability and security are central to any architecture I design. Recently, at a retail company, I implemented auto-scaling groups on AWS EC2 instances, which handled peak loads efficiently during Black Friday sales. For security, we adopted IAM roles and VPC configurations to isolate environments. We used AWS CloudTrail for monitoring and compliance. Our efforts resulted in zero downtime and a 15% increase in transaction processing speed. Regular security audits and load testing ensured our architecture met rigorous standards."

Red flag: Fails to mention specific security measures or scalability techniques, or provides generic solutions without depth.


Q: "What role do cloud-native services play in your architecture designs?"

Expected answer: "Cloud-native services are integral to my architecture designs. At my last company, we transitioned to a cloud-native architecture using AWS services like S3, DynamoDB, and ECS. This shift improved our system's agility and reduced maintenance overhead by 30%. By leveraging managed services, we focused more on innovation than infrastructure management. This strategy resulted in quicker deployments and a 25% cost saving on operations. The use of AWS CloudFormation for infrastructure as code further streamlined our deployment process."

Red flag: Candidate does not differentiate between cloud-native and traditional services or lacks real-world examples of cloud-native adoption.


3. Stakeholder Communication

Q: "How do you communicate complex technical concepts to non-technical stakeholders?"

Expected answer: "In my role at an e-commerce company, I frequently presented to non-technical stakeholders. I used analogies and visual aids like PowerPoint and Prezi to simplify complex concepts. For instance, I compared our data integration process to a supply chain, making it relatable. This approach improved stakeholder understanding and buy-in, as reflected in our NPS scores, which increased by 15%. Effective communication also involved active listening, ensuring stakeholder concerns were addressed promptly."

Red flag: Candidate focuses solely on technical jargon or lacks examples of adapting communication style.


Q: "Describe a time you had to resolve a conflict between technical and business teams."

Expected answer: "At my previous company, there was a conflict over resource allocation between our dev team and sales. The dev team needed more time for testing, while sales pushed for faster releases. I facilitated a joint workshop, using Trello to prioritize features based on impact and feasibility. This led to a compromise where critical features were accelerated while ensuring adequate testing time. The collaboration reduced friction and improved our release cycle efficiency by 20%."

Red flag: Candidate cannot provide concrete examples or lacks strategies for conflict resolution.


4. Trade-off Reasoning

Q: "How do you approach cost-benefit analysis when selecting technology?"

Expected answer: "In my role at a fintech startup, cost-benefit analysis was crucial for technology selection. We evaluated AWS and Azure for cloud services. Using AWS Pricing Calculator, we projected costs for both platforms over five years. Despite Azure's initial lower cost, AWS offered superior scalability and support for our specific use cases, which was pivotal. This decision supported our growth trajectory, reducing our three-year TCO by 18% and enhancing system reliability."

Red flag: Candidate lacks experience with cost analysis tools or cannot justify technology choices with data.


Q: "Give an example of a time you had to balance performance and cost."

Expected answer: "Balancing performance and cost was critical at my last enterprise SaaS job. We needed to optimize our database queries without escalating costs. We opted for PostgreSQL with Amazon RDS, using read replicas to distribute load efficiently. This strategy improved query performance by 30% while keeping our budget in check. Our database costs only increased by 10%, a worthwhile trade-off for the performance gains. Regular performance tuning and cost monitoring ensured sustainability."

Red flag: Candidate emphasizes cost-cutting over performance without acknowledging potential trade-offs.


Q: "How do you handle compliance and regulatory considerations in your architecture?"

Expected answer: "At my last company, we developed a healthcare platform compliant with HIPAA regulations. We used AWS services, implementing encryption at rest with KMS and ensuring all data transfers were encrypted. Regular audits using AWS Config and adherence to NIST guidelines were part of our compliance strategy. This meticulous approach resulted in zero compliance breaches over three years and fostered trust with our clients, evidenced by a 20% increase in market share."

Red flag: Candidate lacks familiarity with compliance frameworks or provides overly technical answers without mentioning practical outcomes.


Red Flags When Screening Solutions architects

  • Lacks cloud platform depth — may struggle designing scalable solutions across AWS, Azure, or GCP environments
  • No experience with integration patterns — could fail to effectively connect disparate systems, leading to siloed data
  • Can't articulate cost trade-offs — risks proposing solutions that are financially unsustainable or inefficient
  • Poor stakeholder communication — might struggle to convey technical concepts to non-technical stakeholders, hindering project alignment
  • No API strategy understanding — may design inefficient interfaces, leading to increased maintenance and integration challenges
  • Generic answers without enterprise context — suggests limited hands-on experience or superficial understanding of complex architectures

What to Look for in a Great Solutions Architect

  1. Enterprise architecture expertise — demonstrates ability to design robust systems using established patterns like microservices or event-driven architectures
  2. Cloud proficiency — deep knowledge of AWS, Azure, or GCP, with practical examples of successful deployments
  3. Strong technical discovery skills — excels at uncovering requirements and constraints, ensuring solutions meet business needs
  4. Integration strategy skills — can design seamless data flows across systems using REST, GraphQL, or gRPC effectively
  5. Effective communication — articulates complex technical concepts clearly to diverse stakeholders, ensuring alignment and understanding

Sample Solutions Architect Job Configuration

Here's exactly how a Solutions Architect role looks when configured in AI Screenr. Every field is customizable.

Sample AI Screenr Job Configuration

Senior Solutions Architect — Enterprise SaaS

Job Details

Basic information about the position. The AI reads all of this to calibrate questions and evaluate candidates.

Job Title

Senior Solutions Architect — Enterprise SaaS

Job Family

Engineering

Focus on architectural patterns, integration strategies, and cloud platform expertise for engineering roles.

Interview Template

Strategic Thinking Screen

Allows up to 5 follow-ups per question for in-depth exploration.

Job Description

We're seeking a senior solutions architect to guide enterprise clients through complex technical landscapes. You'll design scalable architectures, lead technical discovery, and ensure seamless integrations across cloud platforms.

Normalized Role Brief

Experienced architect with a focus on enterprise SaaS solutions. Must excel in cloud platforms, integration strategies, and stakeholder communication.

Concise 2-3 sentence summary the AI uses instead of the full description for question generation.

Skills

Required skills are assessed with dedicated questions. Preferred skills earn bonus credit when demonstrated.

Required Skills

Enterprise architecture patternsCustomer technical discoveryCloud platform expertise (AWS, Azure, GCP)Integration and API strategyCost and compliance trade-offs

The AI asks targeted questions about each required skill. 3-7 recommended.

Preferred Skills

Kubernetes and container orchestrationEvent-driven architecture (Kafka)SQL and NoSQL databasesREST, GraphQL, gRPCProposal and whiteboard communication

Nice-to-have skills that help differentiate candidates who both pass the required bar.

Must-Have Competencies

Behavioral/functional capabilities evaluated pass/fail. The AI uses behavioral questions ('Tell me about a time when...').

Architectural Designadvanced

Ability to design scalable and secure enterprise architectures

Stakeholder Communicationintermediate

Effectively convey technical concepts to non-technical stakeholders

Integration Strategyintermediate

Develop robust integration plans that align with business goals

Levels: Basic = can do with guidance, Intermediate = independent, Advanced = can teach others, Expert = industry-leading.

Knockout Criteria

Automatic disqualifiers. If triggered, candidate receives 'No' recommendation regardless of other scores.

Cloud Platform Experience

Fail if: Less than 3 years of professional experience with AWS, Azure, or GCP

Essential for handling complex enterprise environments

Availability

Fail if: Cannot start within 1 month

Immediate need to support ongoing projects

The AI asks about each criterion during a dedicated screening phase early in the interview.

Custom Interview Questions

Mandatory questions asked in order before general exploration. The AI follows up if answers are vague.

Q1

Describe a challenging integration project you led. What were the key considerations?

Q2

How do you approach cost optimization in a cloud architecture?

Q3

Tell me about a time you had to balance technical and business trade-offs.

Q4

How do you ensure compliance in a multi-cloud environment?

Open-ended questions work best. The AI automatically follows up if answers are vague or incomplete.

Question Blueprints

Structured deep-dive questions with pre-written follow-ups ensuring consistent, fair evaluation across all candidates.

B1. How would you architect a scalable solution for a global SaaS platform?

Knowledge areas to assess:

Scalability principlesCloud-native servicesData consistency modelsSecurity and complianceCost management

Pre-written follow-ups:

F1. What specific AWS services would you leverage?

F2. How do you ensure data consistency across regions?

F3. What are your strategies for cost control?

B2. Explain your approach to technical discovery for a new client.

Knowledge areas to assess:

Client needs assessmentTechnical requirement gatheringSolution alignmentRisk identificationStakeholder engagement

Pre-written follow-ups:

F1. How do you prioritize client requirements?

F2. What tools do you use for discovery sessions?

F3. How do you manage stakeholder expectations?

Unlike plain questions where the AI invents follow-ups, blueprints ensure every candidate gets the exact same follow-up questions for fair comparison.

Custom Scoring Rubric

Defines how candidates are scored. Each dimension has a weight that determines its impact on the total score.

DimensionWeightDescription
Architectural Design25%Depth of understanding in designing scalable and secure architectures
Cloud Platform Expertise20%Proficiency in AWS, Azure, or GCP environments
Integration Strategy18%Ability to develop effective integration plans
Stakeholder Communication15%Clarity and effectiveness in communicating with stakeholders
Problem-Solving10%Approach to resolving architectural challenges
Technical Discovery Skills7%Effectiveness in gathering and analyzing client requirements
Blueprint Question Depth5%Coverage of structured deep-dive questions (auto-added)

Default rubric: Communication, Relevance, Technical Knowledge, Problem-Solving, Role Fit, Confidence, Behavioral Fit, Completeness. Auto-adds Language Proficiency and Blueprint Question Depth dimensions when configured.

Interview Settings

Configure duration, language, tone, and additional instructions.

Duration

45 min

Language

English

Template

Strategic Thinking Screen

Video

Enabled

Language Proficiency Assessment

Englishminimum level: C1 (CEFR)3 questions

The AI conducts the main interview in the job language, then switches to the assessment language for dedicated proficiency questions, then switches back for closing.

Tone / Personality

Professional and insightful. Push for specifics and challenge assumptions respectfully.

Adjusts the AI's speaking style but never overrides fairness and neutrality rules.

Company Instructions

We are a leading enterprise SaaS provider with a focus on innovation and customer success. Remote-first with a global client base.

Injected into the AI's context so it can reference your company naturally and tailor questions to your environment.

Evaluation Notes

Prioritize candidates who demonstrate strategic thinking and can articulate the reasoning behind their architectural choices.

Passed to the scoring engine as additional context when generating scores. Influences how the AI weighs evidence.

Banned Topics / Compliance

Do not discuss salary, equity, or compensation. Do not ask about other companies the candidate is interviewing with. Avoid unrelated personal questions.

The AI already avoids illegal/discriminatory questions by default. Use this for company-specific restrictions.

Sample Solutions Architect Screening Report

This is what the hiring team receives after a candidate completes the AI interview — a comprehensive evaluation with scores, evidence, and recommendations.

Sample AI Screening Report

Thomas Lee

84/100Yes

Confidence: 88%

Recommendation Rationale

Thomas exhibits robust expertise in cloud platforms, particularly AWS, with a strong grasp of architectural design patterns. However, his experience with proactive risk management and cost analysis needs further exploration. Recommend proceeding to the next round focusing on these areas.

Summary

Thomas showcases strong cloud platform skills, especially in AWS, and solid architectural design capabilities. His understanding of API strategies is commendable. Needs to deepen skills in risk management and cost analysis.

Knockout Criteria

Cloud Platform ExperiencePassed

Extensive experience with AWS, meeting the requirement.

AvailabilityPassed

Candidate available to start within 3 weeks.

Must-Have Competencies

Architectural DesignPassed
90%

Strong demonstration of microservices and serverless patterns.

Stakeholder CommunicationPassed
85%

Clear and effective communication across diverse teams.

Integration StrategyPassed
80%

Solid grasp of API integration strategies and tools.

Scoring Dimensions

Architectural Designstrong
9/10 w:0.25

Showed deep knowledge of microservices and serverless architecture.

In our last project, I designed a microservices architecture using AWS Lambda and API Gateway, reducing deployment times by 40%.

Cloud Platform Expertisestrong
8/10 w:0.20

Demonstrated extensive AWS experience with EC2, S3, and RDS.

We utilized AWS RDS for a scalable database solution, which improved our query performance by 30%.

Integration Strategymoderate
8/10 w:0.20

Good understanding of API strategies with REST and GraphQL.

I led the integration of REST APIs with GraphQL for a unified data schema, enhancing data retrieval efficiency by 25%.

Stakeholder Communicationmoderate
7/10 w:0.20

Effective communicator with technical and non-technical stakeholders.

I regularly present architecture designs to both technical teams and executive management, ensuring alignment on project goals.

Technical Discovery Skillsstrong
8/10 w:0.15

Proficient in uncovering client requirements and technical needs.

For a recent client, I identified key technical requirements by conducting detailed discovery sessions, reducing project scope creep by 20%.

Blueprint Question Coverage

B1. How would you architect a scalable solution for a global SaaS platform?

microservices architecturecloud-native servicesscalability strategiesmulti-cloud strategies

+ Detailed explanation of AWS scalability features

+ Discussed serverless benefits

- Did not cover multi-cloud considerations

B2. Explain your approach to technical discovery for a new client.

requirement gatheringstakeholder interviewspain point analysis

+ Emphasized structured discovery sessions

+ Highlighted risk identification techniques

Language Assessment

English: assessed at C1 (required: C1)

Interview Coverage

87%

Overall

4/4

Custom Questions

90%

Blueprint Qs

3/3

Competencies

5/5

Required Skills

3/5

Preferred Skills

100%

Language

Coverage gaps:

Multi-cloud experienceCost analysis skillsProactive risk management

Strengths

  • Proficient in AWS with practical use cases
  • Strong architectural design skills
  • Effective stakeholder communication
  • Solid grasp of integration strategies

Risks

  • Limited experience with cost analysis
  • Needs more focus on risk management
  • Did not address multi-cloud strategies

Notable Quotes

In our last project, I designed a microservices architecture using AWS Lambda and API Gateway, reducing deployment times by 40%.
We utilized AWS RDS for a scalable database solution, which improved our query performance by 30%.
I led the integration of REST APIs with GraphQL for a unified data schema, enhancing data retrieval efficiency by 25%.

Interview Transcript (excerpt)

AI Interviewer

Hi Thomas, I'm Alex, your AI interviewer for the Solutions Architect position. Let's explore your experience in cloud architecture. Ready to start?

Candidate

Absolutely, I've been working in cloud architecture for over nine years, focusing heavily on AWS solutions for enterprise SaaS applications.

AI Interviewer

Great. How would you architect a scalable solution for a global SaaS platform?

Candidate

I'd use a microservices architecture with AWS services like Lambda and API Gateway to handle dynamic scaling, ensuring low latency across regions with CloudFront.

AI Interviewer

Interesting approach. How do you ensure the system remains cost-effective while scaling?

Candidate

By leveraging AWS's pay-as-you-go model and using cost monitoring tools like AWS Cost Explorer, we can optimize resource allocation and reduce waste.

... full transcript available in the report

Suggested Next Step

Move forward to a technical deep dive. Concentrate on risk management strategies and cost analysis for cloud solutions. His strong foundation in AWS and architecture suggests these gaps are addressable.

FAQ: Hiring Solutions Architects with AI Screening

What topics does the AI screening interview cover for solutions architects?
The AI covers enterprise architecture patterns, technical discovery, cloud platform expertise, integration strategies, and proposal communication. Customize your assessment to focus on specific skills needed for your role.
Can the AI detect if a solutions architect is inflating their experience?
Absolutely. The AI uses scenario-based questions and adaptive follow-ups to validate real-world experience. Learn more about how AI screening works to ensure authenticity.
How does AI screening compare to traditional solutions architect interviews?
AI screening offers consistency and scalability. It adapts questions based on responses, ensuring a thorough assessment of technical skills, unlike static interview scripts.
Does the AI support different levels of solutions architect roles?
Yes, configure the depth of questions to match junior, mid-level, or senior solutions architects, focusing on relevant skills and responsibilities for each level.
What measures are in place to prevent candidates from cheating?
The AI uses dynamic questioning and scenario-based assessments to minimize the chance of rehearsed answers. Discover more about our approach in how AI interviews work.
How long does a solutions architect AI screening interview typically take?
Interviews usually range from 30-60 minutes based on configuration. For detailed options, check out our pricing plans to see how duration impacts cost.
Can the AI assess a candidate's knowledge of specific cloud platforms?
Yes, the AI can tailor questions to AWS, Azure, or GCP, focusing on platform-specific capabilities and architecture patterns.
How can I integrate AI screening into my current hiring process?
Seamlessly integrate AI screening into your workflow by learning more about how AI Screenr works and its compatibility with existing systems.
Are there customizable scoring options available?
Yes, you can adjust scoring criteria to prioritize skills most relevant to your solutions architect role, such as cloud expertise or stakeholder communication.
What languages does the AI screening support?
AI Screenr supports candidate interviews in 38 languages — including English, Spanish, German, French, Italian, Portuguese, Dutch, Polish, Czech, Slovak, Ukrainian, Romanian, Turkish, Japanese, Korean, Chinese, Arabic, and Hindi among others. You configure the interview language per role, so solutions architects are interviewed in the language best suited to your candidate pool. Each interview can also include a dedicated language-proficiency assessment section if the role requires a specific CEFR level.

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