AI Engineer · Full Journey · Multiple Types

Salesforce — AI Engineer ✅ Passed

Level: Staff-Level

Round: Full Journey · Type: Multiple Types · Difficulty: 6/10 · Duration: 360 min · Interviewer: Unfriendly

Topics: Behavioral, Team Fit, Multi-Agent Orchestration, LLM, Project Deep Dive, System Design, AI/ML Fundamentals, Transformers, Context Engineering, RAG, Grounding, Guardrail, Web Crawler, Concurrency Control, Data Models, Benchmarking, Pipeline Optimization

Location: San Francisco Bay Area

Interview date: 2026-03-09

Summary

Interview Rounds Overview

• Round 1: HR Screening
• Round 2: Hiring Manager Chat
• Round 3: Project Deep Dive
• Round 4: AI/ML Fundamentals
• Round 5: Hands
• Round 6: System Design

Details

My interview process included an HR screening, three virtual interview rounds, and an onsite interview.

Virtual Interviews:

• Hiring Manager: This round was primarily behavioral and focused on team fit. I discussed my experience at Amazon, with the interviewer showing interest in my work related to Multi-Agent Orchestration and LLMs.
• Project Deep Dive: I discussed a complex project I had worked on, emphasizing the architectural challenges and trade-offs involved. I recommend preparing a project architecture diagram to avoid any pauses during the discussion.
• AI/ML Fundamentals: I was asked about ML basics such as F1-Score, the difference between classification and regression, and benchmarking. I also discussed model inference, pipeline optimization, and how to service AI Agents. The remaining questions focused on LLMs, requiring knowledge of Transformers, Context Engineering, RAG, Grounding, and Guardrail.

On-site Interview:

The onsite interview was divided into two main sections:

• Hands-on Mini Project (Coding):

I had to implement a web crawler to scrape a specified site and sort the content as required, then export it into a CSV file. I completed the task in Python in about 10 minutes. I discussed optimization strategies and edge cases with the interviewer, who provided positive feedback. I made sure to verbalize my thought process while coding and adhered to best practices. Sharing insights into how the features are implemented in production was well received.

• System Design (Google Sheets):

The task was to design a web service similar to Google Sheets. The interviewer wanted me to focus on the backend and data models, discussing concurrency control (handling multiple users editing simultaneously), storage layer selection, large-scale data load/save, snapshot backup systems, and database tables.