A consultant’s CV rarely needs to say everything they have ever done. For a specific role or tender, what matters is whether the experience that is genuinely there gets put in front of the reader first, in language that matches what the client is actually asking for.
AI Prompt Profiles can be configured to do exactly that: take a consultant’s existing profile, read the job description you paste in, and reorder and emphasize the real experience around it, without adding anything that was not already there. This post walks through how that kind of profile is built and what it does and does not change.
Watch a CV Get Tailored to a Job Description in Minutes
- A job-tailoring profile does not invent content. It reorders and emphasizes a consultant’s existing CV around a specific job description.
- CV evidence always wins. If the job description asks for a skill, technology, or responsibility that is not in the CV, the prompt is instructed not to add it.
- Each field has its own hard limits, for example a 200-word cap and 4 to 5 bullet points on the summary, so the output stays scannable rather than becoming a rewritten essay.
- The job description changes what is emphasized and in what order, never the underlying facts.
- You do not need to fill in every field. A prompt profile can be configured for just the summary, just the tasks, or all three.
- Running it takes a couple of minutes: paste the job description against a consultant’s existing profile, pick the prompt profile, and optionally generate a CV in your chosen template at the same time.
- The same prompt profile is reused for every job description you paste in, not rebuilt each time.
In this article
- Why tailoring a CV is different from parsing one
- What a job-tailoring profile actually does
- The rule that makes it safe: CV evidence always wins
- The three fields it can be configured for
- Setting up and running a job-tailoring profile
- The actual job-tailoring prompts
- Why this matters beyond one job description
- Frequently Asked Questions
Why Tailoring a CV Is Different From Parsing One
A parsing profile, like the one built for converting DIGIT-TM II CVs into DIGIT-TM III format, is designed to change nothing. It locates a section and copies it exactly as written. A job-tailoring profile works on a different problem entirely: the CV already exists in the system, and the task is to present it well against one specific opportunity.
That means the AI is doing more than extraction. It is choosing what to lead with, what to leave out of a summary that has to stay under 200 words, and which of a consultant’s projects deserve the most emphasis for this particular role. The risk is obvious: give an AI that much latitude and it can start inventing skills, exaggerating scope, or borrowing language straight from the job description whether or not the consultant actually has that experience.
A job-tailoring profile is configured specifically to avoid that failure mode, while still doing the reordering and emphasis work that makes a CV worth reading for a specific role.
Think of it as a different job for the same underlying tool. A parsing profile is trusted because it changes nothing. A job-tailoring profile has to earn that same trust while actually doing work, deciding what to lead with and what to leave out. The prompts behind it are written to make that judgment call in a way that can be checked, not just trusted on faith.
What a Job-Tailoring Profile Actually Does
Configured this way, the AI reads two inputs: the consultant’s existing profile in Sprint CV, and a job description you paste in. It uses the job description to decide what to prioritize, and the CV to decide what is actually true.
Does this add skills the consultant does not have?
No, if the profile is configured correctly. It is explicitly instructed not to introduce, infer, or imply anything not supported by the CV.
If a job description asks for a specific technology, methodology, or responsibility that is nowhere in the consultant’s CV, the profile is instructed to leave it out entirely, not to imply it, and not to borrow the phrase anyway because it sounds relevant. The job description shapes emphasis. It never becomes a source of new facts.
What it does change is order and framing. Experience that closely matches the job description gets pulled to the front. Terminology from the job description is used only where it accurately describes something the CV already evidences, so the summary reads like it was written for this role, without becoming a different CV.
The Rule That Makes It Safe: CV Evidence Always Wins
Every field this kind of profile can be configured for repeats the same underlying instruction, worded slightly differently each time: when the job description and the CV disagree, the CV wins.
“If the job description requests a specific technology, skill, methodology, responsibility, or domain that is not present in the CV, do not add it and do not imply that the candidate has it.”
That instruction matters more in a bid or tender context than almost anywhere else. A CV submitted against a framework contract or an RFP gets checked. A summary that quietly borrows a requirement from the job posting, without the underlying experience to back it up, is the kind of error that surfaces in an interview or, worse, after a consultant has already started on an engagement.
It also protects the recruiter running the tool. Nobody wants to explain to a client why a submitted CV claimed a certification or a technology the consultant never actually used. Building that constraint into the prompt itself, rather than relying on someone to catch it during review, is what makes it realistic to run this at the pace a live bid actually needs.
Does this rewrite the consultant’s whole CV?
No. It reorders and re-emphasizes existing evidence within fixed limits, it does not rebuild the CV from scratch.
The summary stays under 200 words and 4 to 5 bullet points. The project introduction is capped at 30 words. Each task and responsibility bullet stays under 15 words. Those limits keep the output tight and scannable, and they are the same regardless of which job description is pasted in.
The Three Fields It Can Be Configured For
A job-tailoring profile does not have to cover the whole CV. It can be built for just the fields that are worth automating, and left blank elsewhere.
| Field | What it produces | Hard limit |
|---|---|---|
| CV summary | A bullet-point summary of technical expertise and experience, reordered around the job description | 200 words, 4 to 5 bullet points |
| Project description | A short, non-technical introduction to a project’s purpose or mission | 30 words, one paragraph |
| Tasks and responsibilities | Bullet points describing actual activities and deliverables on a project, reordered by relevance | 15 words per bullet |
“Do not force every requirement from the job description into the summary. Include only the most relevant matches supported by the CV.”
That instruction shows up in each of the three prompts in some form. The goal is not to check every box in the job posting. It is to surface the strongest genuine matches first and let the rest of the CV speak for itself.
Does this work if I do not have a job description yet?
Yes. Without one, the profile still organizes the CV, just by general importance rather than by fit to a specific role.
The tasks and responsibilities prompt, for example, falls back to ordering content by its own logical importance to the project when no job description is supplied. That makes the same profile useful for a general refresh of a consultant’s CV, not only for a specific submission.
Setting Up and Running a Job-Tailoring Profile
Building the profile is a one-time step. Running it against a job description takes a couple of minutes per consultant.
- ✓Go to Company Settings and open the AI Review tab
- ✓Click Add AI Prompt Profile and give it a name, for example “Job Prompt”
- ✓Paste the prompt into whichever CV section fields you want it to cover, summary, project description, tasks and responsibilities, or any combination
- ✓Click Save
From there, tailoring a specific consultant’s CV to a specific opportunity works the same way every time.
- ✓Go to the consultant’s profile and click AI Options
- ✓Open the AI Job tab
- ✓Paste the job description
- ✓Select the profile you built from the dropdown menu
- ✓Optionally choose to generate a CV directly in your desired template
- ✓Click the AI Job button
- ✓After a couple of minutes, find the new profile under the profile manager and review the result
The same profile is reused for the next job description, and the one after that. Firms managing CV management for consulting companies across multiple active bids typically keep one or two of these profiles configured and run them per opportunity as it comes in.
The Actual Job-Tailoring Prompts
Here is the real configuration behind each field, in full. Copy any of these into your own AI Prompt Profile as a starting point.
CV Summary Prompt
Instructions:
- Craft a concise and compelling CV summary in bullet points in {PROFILE_LANGUAGE}, based strictly on the provided CV.
- Focus primarily on the person's technical expertise, professional experience, and areas of expertise.
- Mention the person's total years of professional experience in the most relevant fields, based only on evidence in the CV.
- Do not mention languages or educational background.
- Write a maximum of 200 words.
- Use a maximum of 4-5 bullet points.
- Use a line break at the end of each bullet point.
- Do not start any bullet point with "As [job title] at [company]".
- Refer to specific technologies, tools, methodologies, platforms, frameworks, programming languages, or technical domains when they are relevant and explicitly supported by the CV.
- Avoid listing more than 3 technologies or skills consecutively. Integrate technologies naturally into the description of the person's experience.
- Do not introduce, infer, or claim any skill, technology, responsibility, industry experience, seniority, or achievement that is not supported by the CV.
JOB DESCRIPTION OPTIMISATION:
- If a job description is provided, use it to determine which parts of the candidate's CV are most relevant to the target role.
- Prioritise experience, technical expertise, responsibilities, technologies, methodologies, and domains from the CV that directly match or strongly relate to the job description.
- Reorder and emphasise the candidate's existing experience according to its relevance to the job description. The most relevant evidence should appear first.
- Use terminology from the job description when it accurately describes experience that is already evidenced in the CV. Do not copy phrases from the job description if they are not supported by the CV.
- If the job description requests a specific technology, skill, methodology, responsibility, or domain that is not present in the CV, do not add it and do not imply that the candidate has it.
- Give greater prominence to direct matches than to generic or transferable skills.
- When several experiences are relevant, prioritise the most recent and/or strongest evidence from the CV.
- Do not force every requirement from the job description into the summary. Include only the most relevant matches supported by the CV.
- The objective is to maximise the relevance of the summary to the job description while maintaining complete factual accuracy.
SKILL SELECTION:
- Use {FOCUS_SKILLS:5} as input to identify the candidate's most relevant technical expertise.
- Do not automatically include all five focus skills.
- Select only the skills that are meaningful for the target role and supported by substantial evidence in the CV.
- Prefer specific, substantive technical expertise over generic skills such as "communication", "teamwork", "problem solving", "project management", or "training", unless these are specifically important to the target role and strongly evidenced in the CV.
OUTPUT REQUIREMENTS:
- Maximum 200 words.
- Maximum 4-5 bullet points.
- Concise, factual, and technically focused.
- Job-description relevance should influence the ordering and emphasis, not the factual content.
- CV evidence always takes priority over the job description.
Project Description Prompt
Instructions:
- In {PROFILE_LANGUAGE}, create a concise introduction paragraph describing the provided project in the third person.
- Write the introduction as if explaining the project to a non-IT person, using clear and accessible language.
- Maximum 30 words.
- Do not start with "As a [job title] working at [company]" or similar wording.
- Focus on the project's purpose, mission, business objective, or main outcome rather than technical implementation details.
- Ensure all information is derived solely from the details of the provided project.
- Do not invent, infer, or exaggerate the project's purpose, scope, impact, or outcomes.
JOB DESCRIPTION OPTIMISATION:
- If a job description is provided, identify the main mission, objective, or business purpose of the target role.
- Where relevant and factually supported, frame the project introduction around the same or a closely related mission.
- Highlight the aspects of the project's purpose that are most relevant to the mission described in the job description.
- The job description may influence the framing and emphasis of the introduction, but it must never introduce information that is not supported by the project.
- Only establish a connection with the job description when the project genuinely supports it.
- Do not force a connection to the job description when there is no meaningful or factual alignment.
- Never claim that the project had a purpose, responsibility, technology, business objective, or outcome solely because it appears in the job description.
- When there is a conflict between the job description and the project information, always prioritise the project information.
OUTPUT REQUIREMENTS:
- One paragraph only.
- Maximum 30 words.
- Third person.
- Clear and understandable to a non-IT person.
- Describe the project's mission or purpose, not the candidate's responsibilities.
- Keep the wording concise, natural, factual, and strongly aligned with the project evidence.
Tasks and Responsibilities Prompt
Instructions:
- In {PROFILE_LANGUAGE}, outline the individual tasks and responsibilities performed in the provided project using bullet points.
- Each bullet point must describe a specific task or responsibility and contain no more than 15 words.
- Do not use headers to introduce the individual tasks.
- Do not create bullet points that simply enumerate skills, technologies, tools, or methodologies.
- Focus on actual activities, responsibilities, deliverables, and outcomes described in the project.
- Refer to the technologies, tools, platforms, frameworks, methodologies, or programming languages used when they are directly relevant to the task and explicitly supported by the project information.
- Where appropriate, integrate the technology naturally into the task rather than listing it separately.
- Ensure every task and responsibility is derived solely from the details of the provided project.
- Do not invent, infer, exaggerate, or generalise responsibilities that are not explicitly supported by the project information.
JOB DESCRIPTION OPTIMISATION:
- If a job description is provided, use it to determine the relevance of each task and responsibility to the target role.
- Prioritise and place first the tasks and responsibilities that are most relevant to the job description.
- Reorder the existing project responsibilities according to their relevance to the job description.
- Give priority to direct matches between the project experience and the responsibilities, technologies, methodologies, or domains requested in the job description.
- Use terminology from the job description when it accurately reflects a responsibility already evidenced in the project.
- Do not create a responsibility simply because it is mentioned or required in the job description.
- If a responsibility, technology, methodology, or domain from the job description is not supported by the project, do not include it.
- Do not force all job requirements into the output. Only include responsibilities that are genuinely supported by the project.
- The job description should influence the ordering and emphasis of the tasks, but never change the factual content of the project.
- If no job description is provided, organise the tasks in the most logical order based on their importance and relevance to the project.
OUTPUT REQUIREMENTS:
- Every bullet point must contain no more than 15 words.
- Use bullet points only, without section headers.
- Each bullet point must describe a meaningful task or responsibility.
- Prioritise concrete responsibilities over generic statements.
- Avoid skill-only or technology-only bullet points.
- Maintain complete factual accuracy based on the provided project.
Why This Matters Beyond One Job Description
A single consultant can reasonably be submitted for more than one opportunity, and a fresh job description does not mean starting the CV over. The same profile can be run again with a different job description pasted in, and the underlying facts about the consultant stay exactly the same. Only the emphasis moves.
For a bid team working several active opportunities at once, that turns a task that used to mean rewriting a summary by hand, for every submission, into a paste-and-run step. The profile itself, along with any parsing or interview-notes profiles a firm has already built, lives in the same AI Prompt Profiles library inside Enterprise CV Manager.
It is worth building more than one variant if a firm regularly bids into different kinds of roles, a profile tuned for technical delivery positions reads differently from one tuned for a program management submission, even against the same underlying consultant pool. The prompt fields above are a starting point, not a fixed script, and the word limits, tone, and skill-selection rules can all be adjusted to match how a firm’s own bid team writes.
Explore More
See What Else an AI Prompt Profile Can Do
Job tailoring is one configuration. The same capability is also being used to:
See the full picture in AI Prompt Profiles: Match AI CV Review to Every Workflow.
Frequently Asked Questions
Can an AI Prompt Profile tailor a CV to a job description in Sprint CV?
Yes. It is configured with prompts that reorder and emphasize a consultant’s existing CV content around a pasted job description, without inventing new skills or experience.
Does it invent skills the consultant does not have?
No, when configured as described here. The prompts explicitly instruct the AI not to add, infer, or imply any skill, technology, or responsibility that is not already supported by the CV.
Does it rewrite the whole CV, or just reorder it?
It reorders and re-emphasizes existing content within fixed limits, such as a 200-word cap on the summary. It does not compose a new CV from scratch.
What happens if the job description asks for something the CV does not support?
That requirement is left out. The prompts are written so the CV always takes priority over the job description whenever the two do not align.
Do I have to configure all three fields, summary, project description, and tasks?
No. It is not mandatory to use a prompt on every field. You can configure only the sections you actually want automated and leave the rest as they are.
Can I reuse the same prompt profile for different job descriptions?
Yes. The prompt profile is built once and reused every time, with a new job description pasted in against a consultant’s AI Job tab for each opportunity.
Final Thought
Matching a consultant to a job description is not the same job as parsing a CV into a new template, and it should not be built the same way. A job-tailoring prompt profile is allowed to shape and reorder, but never to invent, and that distinction is what keeps a tailored CV honest.
It is one more configuration built on AI Prompt Profiles, alongside parsing and interview-notes cases, for the specific moment a consultant’s CV needs to speak to one opportunity without becoming a different CV.
Curious what an AI Prompt Profile built to tailor CVs to your own bids and job descriptions would look like? Book a demo with Marco Pincho to walk through your specific case.
About the Author
Seven years of watching recruiters format the same CV three different ways for three different clients led Marco Pincho to build Sprint CV, an enterprise CV manager used by companies including VASS, Fujitsu, Sword Group, and Expleo to standardize CV creation and submission. He holds an Executive Master in IT Management from Solvay Brussels School and spends most weeks on calls with recruitment leaders and HR directors, working through documentation problems like the one covered in this article. Connect with Marco on LinkedIn
