Claude Certified Architect - Professional
Own the full lifecycle of secure, observable, production-grade Claude systems from discovery to iteration.
Mid- to senior-level solution architects, AI engineers, technical leads, and senior software engineers responsible for end-to-end production systems and cross-functional decisions.
63
Questions
120 min
Time limit
$175
Exam fee
720 / 1000
Passing score
Multiple-choice and multiple-response
Format
Proctored online or at a test center
Delivery
12 months
Validity
v1.0 · July 2026
Guide
Exam domains
Weighted objectives straight from the exam guide.
Solution Design and Architecture
17%- Translate business problems into Claude solutions
- Design input, processing, output, and feedback loops
- Choose workflow, agentic, or augmented-LLM patterns
- Design multi-agent orchestration
- Decompose complex problems
- Align designs to value, cost, performance, and SLAs
Claude Models, Prompting and Context Engineering
13%- Select models from explicit tradeoffs
- Design prompts, templates, and guardrails
- Apply zero-shot, few-shot, and reasoning techniques
- Manage context windows and token use
- Reuse stable prompts with caching, modular prompts, and Skills
Integration
19%- Reduce capability bloat
- Find authentication and authorization gaps
- Balance accuracy and latency
- Select observability at scale
- Design RAG chunking and indexing
- Match retrieval to data shape and query pattern
- Choose MCP, API, CLI, or agent-to-agent integration
- Use progressive discovery instead of monolithic context where appropriate
Evaluation, Testing and Optimization
16%- Define accuracy, latency, cost, safety, and security metrics
- Build representative datasets and mixed-method test frameworks
- Run A/B tests and iterative improvements
- Diagnose prompt, hallucination, retrieval, and model failures
- Optimize tokens, latency, and cost-performance
- Monitor with logs, traces, and observability
Governance, Safety and Risk Management
14%- Layer guardrails and safety controls
- Identify LLM failure modes
- Design human-in-the-loop validation
- Account for GDPR, HIPAA, FedRAMP, and applicable regulation
- Address bias, fairness, and transparency
Stakeholder Communication and Lifecycle Management
14%- Run structured discovery
- Communicate decisions and tradeoffs
- Manage feedback, expectations, and SLAs
- Document architectures and implementation guidance
- Support discovery, design, handoff, monitoring, and iteration
Developer Productivity and Operational Enablement
7%- Configure Claude tools and team environments
- Improve engineering workflows with AI-assisted tooling
- Support debugging and operational incident resolution
Study path · 25 lessons
Go deeper in the main curriculum
Production LLM Application
Connect model calls to a service boundary
Advanced RAG
Go deeper on retrieval and reranking
LLM Observability
Instrument production trajectories
A/B Testing LLM Features
Compare variants with live evidence
SRE for AI
Own incidents, SLOs, and recovery
Compliance Frameworks
Map obligations to system controls
FinOps for LLMs
Manage cost per useful outcome