Hello Reader,

One of my bootcamp students just landed a Forward Deployed Engineer role at Google. He came from an Oracle Cloud background with AWS knowledge. He doesn't have a PhD, or a master's degree.

If you have been staring at FDE job postings feeling underqualified, his path is worth understanding before you count yourself out.

Here is the exact breakdown of Google's FDE interview process, straight from Google's own posted description of the role, plus what it takes to actually get through each round.

Understand the role before you understand the interview

Google describes this role as an embedded builder who bridges the gap between frontier AI products and production-grade reality within customers. It is dual-purpose by design. You are providing white-glove deployment of AI systems, and you are acting as a feedback loop that turns real-world field insights into Google Cloud's product roadmap.

This is not a heads-down engineering role. It combines customer-facing executive communication with genuinely deep GenAI and technical work.

If you look at the qualifications list, it can look intimidating. PhD-level language, deep GCP experience requirements, all of it. Do not let that stop you from applying.

If you have 70 to 80 percent of the listed qualifications and a strong body of work to back it up, you will get the interview call.

My student proved this directly. Strong Oracle Cloud background, working AWS knowledge, and a body of work good enough to get him through the door with zero GCP experience.

Round one: the recruiter screen

This is longer than a typical 10 to 15 minute screening call. Regular customer engineer or TAM interviews at Google run six rounds. FDE has fewer total rounds, which means the recruiter screen has to do more work up front to confirm you are the right candidate to move forward.

Remember the responsibility description: this is not a dungeon developer role. Being technically excellent at AI engineering is not enough on its own. You need to demonstrate executive voice combined with technical keywords, and you need to be able to explain the actual business impact of your projects to a customer. Nail that combination in the recruiter screen and you move forward.

Round two: the coding round

Sixty minutes. Based on published candidate data, expect a LeetCode medium-level problem. This is where the equation becomes clear: FDE equals Solutions Architect skills, plus GenAI knowledge, plus coding ability.

Every major company hiring for FDE roles right now, Google, OpenAI, Palantir, tests coding directly. If you are targeting FDE, you need to be able to code.

You are not allowed to use AI for the leetcode round.

Round three: the agentic system design round

This is the round that separates candidates who have studied concepts from candidates who have only studied cloud architecture. You will be tested on both cloud architecture and agentic system design, not one or the other.

Expect deliberately vague prompts. Something like: "Can you create an application that does e-commerce order processing and uses an agent to solve a problem?" The vagueness is intentional, because it mirrors real customer conversations.

Enterprises frequently do not know what AI can actually do for them yet. You need to spend the first 7 to 10 minutes asking discovery questions before jumping into a solution, exactly like a system design interview. What are today's pain points? How much time is this taking? Is the bottleneck latency or cost? Hone in based on the answers.

Once you start designing, the interviewer is listening for keywords because the round moves fast. If you mention a three-tier architecture, be ready to name every component: external load balancer, virtual machines, internal load balancer, database.

Then the conversation shifts to the agentic side. What orchestration pattern are you using, loop, sequential, or hierarchical, and why one over another? If latency is the stated challenge, how does your agentic architecture actually address it?

Around 20 to 30 minutes of this round focuses specifically on agentic orchestration and patterns, and you will not get much time per topic, so study the vocabulary in advance: MCP versus A2A, security, RAG deep dive, performance evaluation, and sample implementation.

You will also be asked how you would actually implement your proposed orchestration in code. Knowing Python alone is not enough here, because implementing agentic patterns from scratch in plain Python or Java requires heavy custom coding. Frameworks like LangChain, LangGraph, or AWS Strands have these patterns built in already, including built-in observability so you can trace execution from code to LLM to tools to RAG without building that monitoring yourself.

One more thing worth internalizing: not knowing GCP services specifically is not disqualifying. Interviewers at every major tech company are looking for people who understand the underlying concepts, agent orchestration, security for agentic systems, these have nothing to do with which cloud you used to learn them.

If you understand the concepts and can demonstrate implementation on any one cloud, you can transfer that into any big tech interview.

Round four: the "Googliness" round

Sixty minutes, fully behavioral. Study Amazon-style leadership principles, but specific to Google's version, and practice them the same way you would practice for any behavioral round: real stories, real outcomes, connected to the specific principle being tested.

Every round in this process matters independently. Passing the agentic system design round does not save you if you fail the Googliness round. The same rule applies at OpenAI. Passing the take-home problem and the agentic design round does not matter if you fail calibration and behavioral rounds. Do not treat behavioral prep as an afterthought relative to the technical rounds.

The bigger lesson underneath all four rounds

The skill stack that gets you through an FDE interview, cloud architecture, system design, GenAI, agentic patterns, executive communication, and behavioral readiness, is not narrow to FDE roles. It is the same stack that opens doors to general Solutions Architect roles, AI Architect roles, and GenAI Specialist SA roles.

Do not over-focus on one specific job title. Build the underlying skill set, and you become a fit for a wider range of roles than you might expect.

Keep learning and keep rocking 🚀,

Raj

P.S - If you want to get an AWS Solutions Architect job without coding or learning every AWS service, the 10th cohort for AWS SA Bootcamp is launching on Oct 17th, 12 PM ET (Eastern Time) via live workshop. This program now includes our updated Gen AI curriculum. Please register below:

Here’s what you get when you show up LIVE:

1. The myths keeping most people stuck - and what actually gets you hired as an SA - I've conducted over 300 SA interviews, so I know what I'm talking about!
2. How GenAI is reshaping the SA and Gen AI roles such as FDE, and the exact AI concepts (RAG, agents, MCP, eval etc.) you need to speak fluently in interviews.
3. A first look at my new product feature, built to help you practice real-world, interview-relevant hands-on work instead of copy-paste tutorials.
4. Full bootcamp breakdown for Cohort 10, plus a special offer only for live attendees.
5. My exclusive Solutions Architect framework to prep you for today's job market! But if you’re not live, you won’t get it. No second chances.

And good news - it already worked for last cohort's students who secured cloud jobs in top companies, including at AWS, Microsoft, Google, JPMorgan, Reddit, and some of them didn't even have cloud experience 💰.

Spots are limited, so don't miss it!