# What FDE recruiters look for: code gets you in, customer communication sets the ranking

> You cannot work as an FDE without coding. Once candidates have shown they can code, what decides who gets hired is how well they communicate with customers and win them over.

Bản gốc: https://fdetimes.net/en/guides/what-fde-recruiters-look-for/

FDE recruiters look for three layers of skill: programming broad enough to pass screening, customer communication that decides how you are ranked, and the ability to take ownership of an entire deployment. An analysis of about 1,000 FDE job postings shows that if you cannot code, you will not get in. Most postings require Python along with full stack experience, and 47% state that candidates must work directly with customers.

AI and ML knowledge is increasingly in demand: 35% of postings mention agents and 31% require LLM experience. Taken together, these numbers describe a very different candidate from a pure backend engineer: someone who can write both front-end and backend code, understands LLMs and agents well enough to build systems with them, and can hold their own in a meeting room with customers.

## The technical layer: the threshold for consideration

Paraform lists the core FDE skill set as a backend language, cloud infrastructure, data engineering, applied AI and customer communication. A concrete example from the employer side: Palantir's posting for a Forward Deployed Enablement Engineer asks for proficiency in one or more programming languages or data engineering frameworks.

| Skill area | Signal in job postings | Level needed to pass screening |
|---|---|---|
| Programming | Mandatory; most postings require Python | Write production code, not just scripts |
| Full stack | Most postings require front-end | Build a demo UI for the customer without waiting for an FE team |
| Cloud & data engineering | Part of the core skill set Paraform lists | Deploy and run pipelines on the customer's infrastructure |
| Applied AI | 35% mention agents, 31% require LLMs | Integrate LLMs/agents into real workflows, not stop at a prototype |

The list covers many layers of a system rather than going deep in one area. If you work in backend today, score yourself against each row of the table: which rows you can back with evidence from real work, and which you have only read about. The rows without evidence are the gaps to close before you apply.

## The customer layer: what ranks candidates

Technical skill is the floor, not the ranking criterion. When two candidates both clear the coding bar, recruiters separate them on communication. Paraform ranks three soft skills as the most important: stakeholder management, adapting to ambiguity, and being comfortable switching between many contexts.

Communication here does not mean presenting slides. A typical requirement is persuading a customer's engineering team to accept your architecture recommendation. Your audience is engineers. They have their own systems and no particular reason to listen to an outsider. Winning them over takes deep enough technical understanding and the ability to read what each party wants.

## The ownership layer: owning the whole deployment

The third requirement is owning the entire deployment, including when something breaks at 2 a.m. Palantir's Enablement Engineer posting puts the same idea in different words: learn continuously, work independently, and make decisions with minimal supervision.

These two requirements explain why an FDE needs full stack skills and both cloud and data experience. The person trusted to decide with minimal supervision is also the person who has to fix things alone when the system goes down. Technical breadth is not for show; it is what lets one person handle a whole deployment.

**Điểm mấu chốt:** FDE recruiters are not looking for the best engineer in one specialism. They are looking for someone who can take sole responsibility for results at the customer's site.

## Showing all three layers on your CV

If your CV only lists your stack, it proves only the first layer. Three ways to make it speak to all three:

- Write up each project as: the customer's problem, the technical decision you made, how you persuaded the people involved, and the result. A single line like that shows all three skill groups at once.
- For applied AI, a project that integrates an LLM or agent into a real business workflow, however small, is worth more than a certificate.
- If you have never worked in a customer-facing role, look through your current job: times you worked directly with a partner's team, times you changed an architecture because of feedback from internal users, times you were on call for an incident and made the decisions yourself. That is material for layers two and three.

Written communication is a skill you can practise in your current job. Write a short design doc explaining a technical decision to people outside your team, then ask for feedback.

**Thử ngay tuần này:**

- Pick 3 FDE job descriptions, underline every sentence about customer-facing work, stakeholders and ambiguity, then write a real example from your own work for each one.
- Build a small full stack demo (Python backend + simple UI) that calls an LLM or agent to solve a specific business problem, deploy it to the cloud and write down your architecture decisions.

## Nguồn

- [What I learned analyzing 1K forward deployed engineer jobs (Bloomberry)](https://bloomberry.com/blog/i-analyzed-1000-forward-deployed-engineer-jobs-what-i-learned/)

- [What is a forward deployed engineer? A complete guide | Paraform](https://www.paraform.com/insights/what-is-a-forward-deployed-engineer)

- [Palantir Technologies - Forward Deployed Enablement Engineer - Customer Success](https://jobs.lever.co/palantir/4cba9c95-d16f-440d-83e7-2352480f689f)