FDE at C3 AI: reading four job postings with the same title, and tailoring your CV to the right one

Open C3 AI’s careers page and you will find at least four postings with the title Forward Deployed Engineer: one in London, a Federal role in Tysons (Virginia), an onsite role in Lexington Park (Maryland) and a Defence role in the UK.

The title is identical, but the entry conditions differ so much that someone who qualifies for one can be rejected from another before anyone reads the skills section.

Skimming for familiar technology names and clicking apply is the surest way to waste effort on an FDE role, because postings often mix legal conditions, experience thresholds and skills into a single list.

Aced (formerly Exponent) notes that an ATS often filters FDE CVs before a person reads them. A CV that does not match the specific posting risks stopping right there.

This article uses C3 AI as an example to practise a skill that works at any company: read the posting in layers, then match each line against evidence in your CV.

One job title, four different doors

The London posting describes the core work as building full-stack, AI-enabled enterprise applications on the C3 AI Platform. The onsite role in Lexington Park leans heavily towards operations: keeping the platform stable, with the highest possible uptime, in an on-premises environment separated from the customer’s network.

The work differs, and who is allowed to do it differs even more.

Variant	Experience threshold	Hard conditions / specific preferences
London	2+ years of professional software development in an object-oriented language, STEM bachelor’s degree	In the London office 5 days a week; JavaScript and Python preferred
Federal (Tysons, VA)	Level not stated here; read the original posting	US citizenship required; TS/SCI with CI Polygraph is a plus
Onsite Lexington Park, MD	Level not stated here; read the original posting	US citizenship and an active Secret clearance required; full-time at a government facility
Defence (UK)	5+ years in an object-oriented language	Hold, or be able to obtain and maintain, SC/NATO clearance; usually needs 5 years of continuous UK residence

The “not stated” cells for the two Federal roles do not mean those postings set no experience threshold. Before applying, reread the original posting or ask the recruiter; do not assume anyone can get in.

The table shows that skills only decide the outcome once you have cleared the other conditions. An engineer who is excellent at JavaScript but lacks US citizenship has no chance at either Federal role, however good their code.

Reading a job posting in three layers

The first layer is hard conditions: citizenship, clearance, length of residence, office attendance. These are not negotiable and should be read first. The line “This role requires U.S. citizenship” in the Federal posting has only two answers, yes or no; it is not a skill you can learn.

Read this layer slowly, too. The Defence role needs SC clearance, and according to Security Cleared Jobs, SC usually requires 5 years of continuous UK residence immediately before applying, but not necessarily British citizenship. A skim reader can easily rule themselves out by assuming clearance means citizenship.

The second layer is mandatory thresholds: degrees and years of experience. The same person may fit the London role but not yet the Defence one, because 2 years and 5 years are very different bars. Note the wording: the experience must be professional software development in an object-oriented language, not total years in work.

The third layer is preferred skills, such as JavaScript and Python in the London posting. Missing a few lines here does not stop you applying. But once you have cleared the first two layers, this is the only part you can still improve yourself, so it deserves your effort.

Example: a backend engineer with three years’ experience targets the London role

Imagine Minh, an engineer with three years of writing Java for a backend system, who occasionally fixes React front ends, holds an engineering degree, has the right to work in the UK and is happy to be in the office all week. Minh clears layers one and two of the London posting. What remains is layer three and the job description.

The method is to put two columns side by side: on the left, each requirement in the posting; on the right, a piece of concrete evidence. For the line “2+ years in an object-oriented language”, Minh does not write “3 years of Java” but: “Designed and ran three Java services for the internal operations team, owning everything from the API to deployment.”

For the JavaScript line, a vague bullet such as “knows React” is much weaker than: “Built an order-tracking screen in React, wired directly to an API I wrote myself.” That sentence also proves the word full-stack in the job description, which a list of technologies cannot do.

Aced advises tailoring the CV for each FDE application and matching the posting’s keywords, but only including what you can defend in an interview. So Minh uses the posting’s exact words, “full-stack”, “JavaScript”, “object-oriented”, and each is tied to work Minh can describe in detail.

After this exercise, Minh’s right-hand column has two empty cells: Python, and knowledge of the C3 AI Platform. Those are two concrete tasks for the next month, far clearer than generic advice such as “learn more AI”.

How to prepare for a model-driven platform

The main job of an FDE here is building applications on the C3 AI Platform, so turning up to an interview without knowing what it is would be a waste. The official documentation describes it as a model-driven environment for developing and running enterprise AI applications.

The documentation also says applications start from a common modelling language called the C3 AI Type System. For engineers used to building everything from scratch, this signals a different way of working: read the overview to answer for yourself what the platform handles and what you have to write.

Do not try to memorise the documentation. FDEs build applications for businesses, so being able to explain the platform in plain words is worth more practice than remembering details. Practise saying, in a few sentences, what the Type System is and why starting from a data model changes how you write an application.

Mistakes that get a CV rejected early

The first mistake is sending the same CV to every variant. The Defence role needs 5+ years and SC/NATO clearance; the London role needs 2+ years and five days a week in the office. Sending a CV with three years’ experience to the Defence role wastes both sides’ time.

The second is stuffing keywords to get past the ATS with no story behind them. Matching the posting’s words gets your CV to a human reader, but every line you write can become an interview question.

The third is reading “a plus” as “required”, or the other way round. TS/SCI is only preferred for the Tysons role, but an active Secret clearance is required for the Lexington Park role. Both postings carry the word Federal, and skimming that line is the costliest mistake.

Reading postings in layers is not just for C3 AI. Every FDE posting you meet from now on has the same three layers, and anyone who can separate them in ten minutes will know which role to apply for and what their CV still needs.