Hello, I'm Maneshwar. I'm building git-lrc, a Micro AI code reviewer that runs on every commit. It is free and source-available on Github. Star git-lrc to help devs discover the project. Do give it a try and share your feedback.
No. And thank god, because we have enough of those.
If you've been scrolling LinkedIn lately and seen "Forward Deployed Engineer" pop up next to salaries that made you spit out your cold brew โ you're not hallucinating.
The role blew up because of Palantir, got supercharged by the AI gold rush, and now everyone from Google to Razorpay to your favorite Series B startup is hiring them.
Here's the mental model:
- A regular SWE ships features for millions of users they'll never meet.
- An FDE ships an entire system for one customer whose engineers they're sitting next to, screen-sharing with, and occasionally absorbing the rage of.
It is the difference between cooking for a restaurant and being a private chef who flies to your client's house and cooks while they critique the knife work over your shoulder.
The non-negotiable truth: this is NOT a beginner role
Let's kill the dream early so nobody cries later.
Per the roadmap.sh FDE roadmap, the very first note on the path says it plainly: FDE is not a beginner role.
You're expected to already be a full-stack developer stepping into the role, not someone using it as a launchpad.
Real job postings back this up hard:
- Fiddler wants 5+ years building production-grade ML/AI systems.
- Razorpay asks for 3โ10 years of hands-on engineering, people who've shipped production code and debugged it in live customer environments.
So if you're 6 months into your first bootcamp project... bookmark this, build for three more years, then come back. I'll wait.
The FDE skill tree (or: why you need to be a genuine full-stack threat)
Think of the roadmap as a literal RPG skill tree.
Here's what you have to level up.
1. Core technical skills โ Frontend + Backend + Linux
FDEs need to be proficient in full-stack development, have high agency, and be able to deliver full apps for customers.
Not "I can center a div" full-stack.
More like "I can stand up a frontend, wire the backend, debug the Linux box it's running on, and explain all three to the customer's CTO" full-stack.
2. DSA & System Design
Here's the spicy one.
The roadmap is brutally honest:
DSA is the first gate in FDE interviews. You won't get to show off your AI skills if you don't pass this round.
Translation: yes, you still have to invert the binary tree.
The LeetCode grind doesn't end just because the job title is fancier.
3. AI Engineering skills
This is where 2026 FDEs separate from the pack.
You're expected to be fluent in at least one major cloud platform and know how to deploy infrastructure as code.
On top of that, the AI-flavored JDs want:
- LLM / agentic frameworks: LangChain, LlamaIndex, LangGraph, AutoGen, MCP, RAG. (Fiddler and Razorpay both list these. "Hands-on counts, not just awareness," as Razorpay puts it.)
- Building and orchestrating agents: tool bindings, eval pipelines, human-approval flows.
- Responsible AI: model monitoring, drift detection, explainability, bias detection.
4. DevOps skills ๐ง
FDEs are responsible for proving to customers that what they built won't break or go rogue in production.
That means you own the deploy, the monitoring, and the dreaded hypercare period.
Razorpay literally describes being the "first responder during the 15โ30 day hypercare period post go-live."
Yeah. You build it, you ship it, you carry the pager. ๐
The half nobody warns you about: Customer & Field skills
This is the part that filters out 80% of brilliant engineers.
You can be a 10x coder and still bomb as an FDE because you can't do this half:
| Field Skill | What it actually means |
|---|---|
| Discovery & Scoping | Run the call, gather requirements, sequence the work, and figure out integration complexity before you commit. |
| Tradeoffs | Constantly juggling Scope vs. Speed vs. Quality and explaining the tradeoff to a non-technical stakeholder without making them feel dumb. |
| Business Acumen | ROI, stakeholder management, product feedback loops. You're not just building, you're proving value. |
| Communication | Technical writing, clear updates, managing expectations, "closing ambiguity without hand-holding." |
As Fiddler puts it, you're literally "the technical voice of the customer", embedded with their team, translating their messy reality into clean technical designs, then carrying their feedback back to your own Product and Engineering teams.
Razorpay is even blunter about what it's not:
This is not a pre-sales role. It is not a support role. It is not solutions architecture. You write production code... and you own the outcome end-to-end.
"Okay but show me the money ๐ฐ"
Fair. Based on tracked 2026 hiring data (fdepulse.com):
- FDE base salaries cluster between roughly $135K and $215K, varying by level and metro.
- Hiring is concentrated, a handful of metros and the top ~10 companies hold most of the open roles.
- AI labs and enterprise SaaS drive most new openings, with consulting firms a distant third.
- Lots of companies are hiring their first or second FDE ever, a strong signal that brand-new teams are forming (read: ground-floor opportunity).
Top 10 companies by open FDE roles
| Company | Open Roles | Median Salary |
|---|---|---|
| Deloitte | 44 | $194K |
| 31 | $185K | |
| ZipLine | 11 | $206K |
| Skyline Eco Adventures | 11 | $206K |
| JDA TSG | 10 | $110K |
| Adobe | 5 | $221K |
| Okta | 5 | $275K |
| Tenex.AI | 5 | Not disclosed |
| David Joseph & Company | 5 | $188K |
| C3 AI | 3 | $156K |
Okta out here paying $275K to engineers who can both ship and talk.
Suddenly that public-speaking class doesn't seem like a waste, huh.
Your roadmap to becoming an FDE
If you want to actually chase this, here's the leveling order I'd suggest based on the roadmap:
- Become a genuine full-stack dev first. Frontend, backend, and enough Linux to be dangerous. No shortcuts.
- Grind DSA + System Design. It's the first interview gate. Period.
- Get fluent in one cloud + Infrastructure as Code. Pick AWS, GCP, or Azure and go deep.
- Learn the AI/agentic stack hands-on. Build something real with LangChain/LangGraph/MCP/RAG. "Awareness" gets you rejected.
- Practice the soft stuff like it's a hard skill. Do discovery calls, write docs people actually read, learn to explain tradeoffs to non-engineers.
- Develop high agency. This word shows up everywhere for a reason. FDEs are trusted to own ambiguous problems and just... handle them.
The roadmap also points to four follow-on tracks worth leveling into: Frontend, Backend, DevOps, and AI Engineer.
So... is it for you?
The FDE role is the rare job that rewards engineers who refused to pick a lane.
If you genuinely enjoy building and the messy human reality of why you're building it talking to customers, owning outcomes, carrying the pager and the conversation, this might be the most fun (and best-paid) seat in tech right now.
If you'd rather put on noise-canceling headphones and never speak to a stakeholder again? Totally valid.
Backend Roadmap is right over there, no judgment. ๐ง
Either way ship code, talk to humans, don't let it break in prod.
That's the whole job not just for FDE, applies to all :)
AI agents write code fast. They also silently remove logic, change behavior, and introduce bugs โ without telling you. You often find out in production.
git-lrc fixes this. It hooks into git commit and reviews every diff before it lands. 60-second setup. Completely free.
Any feedback or contributors are welcome! It's online, source-available, and ready for anyone to use.
โญ Star it on GitHub:
HexmosTech
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git-lrc
Free, Micro AI Code Reviews That Run on Commit
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git-lrc
Free, Micro AI Code Reviews That Run on Commit
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AI agents write code fast. They also silently remove logic, change behavior, and introduce bugs -- without telling you. You often find out in production.
git-lrc fixes this. It hooks into git commit and reviews every diff before it lands. 60-second setup. Completely free.
See It In Action
See git-lrc catch serious security issues such as leaked credentials, expensive cloud operations, and sensitive material in log statements
git-lrc-intro-60s.mp4
Why
- ๐ค AI agents silently break things. Code removed. Logic changed. Edge cases gone. You won't notice until production.
- ๐ Catch it before it ships. AI-powered inline comments show you exactly what changed and what looks wrong.
- โฆ
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