💻Criticalmedium20-25 minutes
What's your tech stack? What technologies, tools, and frameworks are you proficient in?
technicaltech-stacktoolsframeworksfull-stackllamaindexgenkitvertex-aibedrockcloud-aicritical
🎯 What Interviewers Are Looking For
- ✓Breadth across full ML/AI stack (frontend, backend, ML, deployment)
- ✓Depth in key technologies with production experience
- ✓Honest assessment of proficiency levels
- ✓Awareness of modern AI/ML ecosystem
- ✓Evidence of continuous learning and adaptation
- ✓Practical application, not just theoretical knowledge
📋 STAR Framework Guide
Structure your answer using this framework:
S - Situation
Your current tech stack and how you've used it
T - Task
Organize by category with proficiency levels
A - Action
Provide concrete examples of usage in projects
R - Result
Show breadth, depth, and willingness to learn new tools
💬 Example Answer
⚠️ Pitfalls to Avoid
- ✗Listing technologies you've only read about, not used
- ✗Claiming 'expert' in everything (not credible)
- ✗Not providing concrete examples of usage
- ✗Focusing only on ML frameworks, ignoring deployment/production
- ✗Being vague about proficiency levels
- ✗Not mentioning what you're currently learning
- ✗Overwhelming with too many tools without depth
- ✗Not knowing when to use frameworks vs raw implementation
💡 Pro Tips
- ✓Organize by category for clarity (ML, Backend, Frontend, Deployment)
- ✓Use proficiency levels: Expert, Advanced, Intermediate, Basic
- ✓Provide concrete project examples for each major tool
- ✓Include metrics where relevant (89% accuracy, 2x speedup)
- ✓Be honest about gaps—shows self-awareness
- ✓Mention what you're actively learning—shows growth mindset
- ✓Prioritize production experience over tutorials
- ✓Ask at the end what's most relevant to their stack
- ✓Discuss framework selection criteria (LlamaIndex vs LangChain vs Genkit)
🔄 Common Follow-up Questions
- →Walk me through your FastAPI project architecture
- →How do you decide between PyTorch and TensorFlow?
- →What's your approach to learning new frameworks?
- →Have you worked with [specific tool in their stack]?
- →What's your experience with Kubernetes?
- →How do you stay current with the fast-moving AI ecosystem?
- →When would you use LlamaIndex vs building RAG from scratch?
- →What's your experience with Genkit? How does it compare to LangChain?
- →How do you choose between different AI orchestration frameworks?
- →When would you choose AWS Bedrock vs Vertex AI vs OpenAI?
- →What's your experience with Google Cloud's AI offerings?
🎤 Practice Your Answer
0:00
Target: 2-3 minutes
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