CV should be organized into clear sections that tell your career story effectively. Below are the essential sections (in order), with notes on what each should contain:
Length expectations in Europe (2026): For senior-level applicants (CTO, Head of AI, Director roles), a two-page CV is commonly accepted and often expected. European CVs are essentially equivalent to US-style resumes and are typically kept concise: “1 page is perfect, 2 are acceptable, 3 are rarely OK”
Modern CV design trends have shifted towards clarity and simplicity, especially in tech. In 2025–2026, the dominant trend is a clean, minimalist layout that emphasizes content over decoration.
Single-Column Format: Use a one-column layout for optimal readability and ATS parsing. While multi-column templates became popular in the 2010s, today they’re seen as less effective.
Standard Sections & Headings: Organize your CV into the familiar sections that tech recruiters expect. Typically, include: Contact Information, a strong Executive Summary/Profile, Skills/Competencies, Work Experience (reverse-chronological), Education, and optionally Certifications/Projects/Publications if relevant. Use conventional headings for these (e.g. “Professional Experience” rather than a creative label) – ATS scanners look for keywords like Experience, Education, Skills to categorize your info.
Bullet Points & White Space: Structure the details of your experience in bullet points (rather than long paragraphs) to improve skim-ability. Each bullet should highlight an accomplishment or responsibility, ideally quantified (e.g. “Implemented X, resulting in Y outcome”). Keep bullet points concise (1–2 lines each) and use 5-6 bullets for recent major roles, fewer for older ones.
In 2026, resume color schemes have trended back toward conservative palettes. The safest approach is a black (or dark gray) text on white background for the body of your CV. You can incorporate a limited accent color to give a modern touch – for example, a subtle navy or teal for headings or to underline your name at the top. If you do use an accent, keep it minimal and professional (avoid neon or overly bright tones) and ensure the CV is still clear if printed in grayscale.
Icons and Symbols: Resume icons (such as little symbols for phone ☎️, email ✉️, or skill graphs) became popular in graphic CV templates, but approach them with caution. Many hiring experts now advise avoiding icons entirely, or using them only in very limited ways, due to ATS and readability concerns.
Outdated Applicant Tracking Systems are still used by many big brands, and those cannot reliably interpret images or icons, so an icon might either be ignored or, worse, interpreted as a random character that garbles your CV’s text. For example, an embedded icon in your experience section could turn into an unrecognizable symbol in the parsed text, potentially messing up how your info appears to recruiters.
Graphics, Logos, and Photos: For tech roles, avoid photos, graphics, or elaborate visuals on your CV. Including a headshot is common in some European countries, but the trend even in Europe is moving away from photos to reduce bias. If you apply for a photo model role, that is a totally different matter.
Stick to Standard Formatting: Use a traditional, simplified format that ATS software can easily parse. This means no text in headers or footers, no tables or multi-column text boxes, and no unusual fonts or encodings.
File Format: Submit in the format requested by the employer. Both PDF and DOCX are generally accepted by modern ATS systems. PDFs preserve your layout and have become largely ATS-safe (Jobscan’s 2025 tests even found PDFs parse slightly more accurately on average).
Keywords & Scannable Text: Design choices should never hide the keywords your CV needs. For senior AI/ML roles (e.g. mentioning “LangChain, transformer models, cloud architecture”), make sure these terms appear as text in your CV (not buried in an image or graphic).
At the very top, include your name and updated contact details:
- Name (full name, bold or larger text).
- Email (professional address) and phone number (optional if you prefer calls).
- LinkedIn URL (since your LinkedIn can provide richer detail).
- Avoid adding a photo, age, or other personal data. They don’t aid your candidacy and can introduce bias.
A brief 3–5 sentence opening summary that highlights your unique value proposition as a leader. This should be tailored to the specific role/industry you target.
State your title or expertise (e.g. “AI Engineering Executive with 15+ years in ML innovation…”).
Emphasize key achievements or specialties (for example, “led enterprise-wide AI transformations” or “built award-winning agentic AI platforms”).
Showcase, for example leadership scope in leadership roles (e.g. teams led, strategic initiatives) and align with 2026 trends (mention AI, digital transformation, etc.). For instance: “Executive leader blending deep AI expertise with strategic vision – spearheaded LLM-driven products impacting millions and drove digital transformation across global teams.” Tailor this summary to address the company’s needs and the role’s focus – it should read like a solution to their problems, not a generic overview.
Core Skills & Expertise: A concise section (possibly a bullet list or inline list) highlighting your technical proficiencies and leadership skills most relevant to the role:
Technical Skills: Include the emerging AI/ML technologies and tools you excel in. In 2026, AI fluency is crucial – mention things like “LLM orchestration (LangChain, Vector DBs)”, “Deep Learning (PyTorch)”, “Generative AI”, and any domain-specific tools. Being explicit is important: employers actively seek AI skills on resumes, so citing “Prompt Engineering, ChatGPT/Claude integration, autonomous agents” can set you apart.
Leadership & Soft Skills: Don’t omit the human skills that are vital for executives. Highlight abilities like strategic planning, team leadership, cross-functional collaboration, communication, and change management. Top candidates combine technical prowess with strong interpersonal skills, so indicate strengths like “stakeholder management”, “mentoring 20+ engineers”, or “bridging business and technology”.
Key Credentials: If relevant, you can include certifications or noteworthy credentials here (e.g. “Ph.D. in Machine Learning”, “MBA”, “AWS Certified Solutions Architect”). This “Core Skills” section helps ensure essential keywords (both technical and leadership) are immediately visible – useful for both human readers and Applicant Tracking Systems (ATS) scanning for specific terms.
This is the heart of your CV: detail your work history in reverse chronological order (most recent role first). For each role, focus on achievements and outcomes, not just duties:
Heading: Include your title, company, location, and years. If the company is not well-known, you can add a one-line description (e.g. “Series B SaaS startup” or “Fortune 500 e-commerce leader”). For senior roles, your most recent position should get the most attention – place it prominently and give it the most detail.
Role Description: 1–2 sentences (optional) summarizing your scope (e.g. “Led a 50-person data science and engineering organization with a $10M budget” – giving context of team size, budget, or mandate). This sets the scene, especially for executive roles.
Bulleted Achievements: 2 to 4 bullet points per role highlighting your key accomplishments. Each bullet should demonstrate impact with metrics or concrete outcomes whenever possible. Use strong action verbs and be specific about technology and results. For example:
“Grew data science team from 5 to 20 and implemented an ML platform that boosted model deployment speed 3×, enabling a 10x efficiency improvement in core operations”.
“Led cross-functional initiative to integrate GPT-4-powered agents into customer support, reducing response time by 60% and improving customer satisfaction by 25%.” In this example, note how the AI tool (GPT-4) and outcome (60% faster) are explicitly stated – this clarity is essential.
“Delivered a company-wide AI transformation (adopting automation and predictive analytics) that cut costs by $2M/year and informed product strategy at the board level.” Each achievement bullet should answer: What did you do? How did you do it (tools/techniques)? and What was the result or value? This demonstrates your real-world impact. Quantify outcomes (revenue gained, % improvements, cost savings, users impacted, etc.) wherever possible. If an accomplishment is in an emerging tech area, make sure to name the tech. For instance, rather than a vague “worked on AI project,” a strong bullet is: “Built an AI-based feedback parser using Claude 3.5 + LangChain; clustered 1,300+ NPS comments into themes for product roadmap planning”. This names the models/tools and the tangible outcome, giving credibility to your AI expertise. (Real-world tip: When describing AI projects, be precise – mention the model or framework, your specific contribution, and the outcome. Hiring managers want to know “what you actually did”, not just buzzwords.)
Leadership & Strategy: In your bullets, also highlight leadership actions: e.g. “Mentored 5 new engineering managers”, “Instilled OKR framework across a 100-person department”, or “Drove AI ethics guidelines adopted company-wide”. Such details show you can operate at the strategic level expected of a Head of AI or CTO.
Ordering: List achievements in order of relevance/impact, and tailor them to what each target employer cares about. Use more bullets for recent roles, and fewer (or a brief summary line) for older positions >10 years ago. For roles older than ~10-15 years, you can abbreviate or even just list title/company/dates unless they are extremely relevant. The goal is to keep the CV focused on your most impactful and recent experience.
Additional note: If you have significant promotions or progression within a company, make that clear (e.g. “Promoted from Senior ML Engineer to Head of AI within 3 years”). This demonstrates career trajectory and leadership growth.
Include your education and any important certifications
List degrees (Ph.D., Masters, Bachelors) with field of study, institution, and year. For senior technical roles, a PhD or research background in AI/ML can be a strong asset; for executive roles, an MBA or management education might be worth noting if relevant. High school is only relevant if that is the highest education you have.
Mention certifications or courses that bolster your candidacy (e.g. “AWS Certified ML Specialty”, “Certified Scrum Master”, or executive leadership programs). In 2026, credentials in digital transformation or AI (for example, an online AI leadership certificate) can signal that you’re up-to-date.
If you have any professional affiliations (like chartered engineer status, membership in an AI consortium) or security clearances relevant to the role, you can include those here or in a separate section. Also list languages spoken if relevant to global roles.
For very senior candidates: The education section is usually kept brief. Your experience will matter more, so don’t devote too much space here. However, do include notable academic honors (e.g. “MIT, M.S. Computer Science – Thesis in Reinforcement Learning”) if it reinforces your AI expertise.
Depending on your background, you may include one or more extra sections if they add real value for the target role. Ensure anything here is relevant and noteworthy, quality over quantity.
Key Achievements / Career Highlights: A short bullet list (3–5 items) at the top of your CV that calls out your most impressive accomplishments across your career. This “highlights reel” can be effective for executive resumes. For example, you might feature a bullet about scaling a product to 10M users, another about a successful AI innovation that won an award, etc. This section essentially teases your biggest wins (especially useful if a recruiter only skims the first page). Make sure these achievements are quantified and linked to business outcomes (growth, revenue, transformation, awards).
Projects or Portfolio: Particularly relevant if you’re an AI expert or applying to a startup or innovation-focused role. A “Projects” section lets you showcase major personal or open-source projects, prototypes, or research work outside of your formal employment. For example, mention that you “Created an open-source AutoGPT agent that garnered 500+ GitHub stars” or “Developed a LangChain-based app as a side project to automate meeting notes”. This demonstrates passion and initiative. Startups love to see side projects and self-driven work, so consider this section if it strengthens your story (especially if you’re targeting smaller companies or roles requiring hands-on technical creativity).
Publications & Patents: If you’re a Head of AI or similar, you may have research papers or patents. A brief section listing key publications (in recognized conferences/journals) or patents can establish your thought leadership and technical depth. This is more important for R&D-centric roles or in Big Tech environments that value innovation.
Awards & Honors: Include notable recognitions – e.g. “Forbes 30 Under 40 in AI”, “Best Tech Manager Award 2025”, or internal company awards. These can validate your excellence and are good conversation starters.
Professional Affiliations/Volunteer: Leadership roles in industry groups (like IEEE, AI associations) or significant community contributions (organizing conferences, speaking at major events) can also be listed if space allows. They demonstrate commitment to the field.
Remember, focus on content that strengthens your fit for the specific role. Omit trivial or outdated items – for example, programming competitions from 15 years ago or unrelated hobbies have no place on an executive CV. Every section should add value or it can be removed (this helps keep your CV concise).