ATS systems used by tech companies scan your resume for specific keywords before any human sees it. Using the wrong terms — or none at all — means instant rejection, no matter how qualified you are. This master list covers the highest-frequency ATS keywords across 6 major IT disciplines, sourced from analysis of 50,000+ real tech job postings in 2026.
💡 How to use this list: Cross-reference with your target job description. For maximum accuracy, use ResumeAIWin to check your exact ATS score free. Only include keywords for skills you actually have — ATS systems verify claims in interviews. For maximum impact, let ResumeAIWin automatically match your resume to each job description and generate a matching cover letter simultaneously — both in 30 seconds.
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Build My Tailored Resume →Don't stuff keywords randomly. ATS systems in 2026 are sophisticated — they evaluate keyword context, not just presence. Include skills in your work experience as achievements: "Deployed containerised microservices on AWS EKS using Terraform, reducing infrastructure costs by 28%."
The most effective approach: use AI to match your specific experience to each job description's exact keyword requirements automatically — rather than manually scanning lists. ResumeAIWin does this in 30 seconds — achieving a 90%+ ATS score guaranteed.
Copying keywords from a list into your resume is not keyword optimisation — it's keyword stuffing, and modern ATS systems in 2026 can identify it. Here's the correct approach to using this keyword list:
Go through this list and mark every keyword that accurately describes your skills, tools you've used, or concepts you understand and could discuss in an interview. Don't add keywords you can't credibly defend in a technical interview — this is both dishonest and counterproductive if you advance past ATS screening.
For each application, read the job description carefully and identify which keywords from this list appear — especially those that appear multiple times or in the required qualifications section. These are the highest-priority terms to include. Keywords that appear in preferred qualifications are secondary targets.
Instead of "Skills: Python, SQL, AWS, Docker" as a flat list, weave keywords into your work experience bullet points contextually: "Built and deployed containerised microservices using Docker and Kubernetes on AWS ECS, reducing deployment time by 65%." This single bullet contains four high-value keywords in a contextual sentence that also quantifies impact.
For critical keywords, include both the abbreviated form and the full form at least once in your resume. "AWS (Amazon Web Services)" in your skills section, and "AWS" elsewhere. ATS systems vary in how they handle abbreviation expansion.
The keywords most commonly missing from software engineering resumes are not the obvious ones — everyone includes Python and JavaScript. The differentiating keywords in 2026 are:
The data science keyword landscape has shifted significantly with the rise of LLMs and MLOps. Keywords that were rare in 2023 are now standard requirements:
Platform engineering has emerged as a distinct discipline separate from DevOps, with its own keyword set. Relevant terms for 2026 include:
Cybersecurity resumes are heavily credential-driven. In addition to technical keywords, certifications carry significant ATS weight. The highest-impact credential terms for 2026:
Understanding what ATS scoring evaluates is one thing. Understanding what recruiters actively search for in candidate databases is another — and for job seekers, the recruiter search query is equally important. When a technical recruiter opens Workday or Greenhouse to find candidates for a role, they typically search by:
Ensure all five of these search dimensions are well-represented in your resume for every application. This is exactly what ResumeAIWin's AI optimises for — it reads the job description and ensures your resume surfaces in every dimension that a recruiter for that specific role would search.
Not all keywords carry equal weight in ATS scoring. Understanding the hierarchy helps you prioritise which terms to include prominently versus which can appear once in a skills list.
These are explicitly listed under "Requirements" or "Must Have" in the job description. Missing even one Tier 1 keyword can drop your score by 10–15 percentage points. Examples: "5+ years Python experience", "AWS certification required", "SQL proficiency required". These must appear in your work experience bullet points — not just in your skills section.
Listed under "Nice to Have" or "Preferred Qualifications." These differentiate candidates who pass the Tier 1 filter. Including 70%+ of Tier 2 keywords can push a 78% score to 90%+. Examples: "Experience with Kubernetes a plus", "Familiarity with dbt preferred", "Agile/Scrum experience desirable."
These are contextual terms that signal sector experience: "FinTech", "B2B SaaS", "enterprise software", "healthcare compliance", "e-commerce platform." They may not be explicitly required but appear throughout the job description and signal cultural and domain fit to both ATS and human reviewers.
Soft skills mentioned in the job description — "cross-functional collaboration", "stakeholder management", "executive communication" — carry less ATS weight individually but contribute to overall match scoring. Include them in your summary and in bullet points where genuinely applicable.
Python, JavaScript, TypeScript, Java, Go (Golang), Rust, C++, C#, Ruby, PHP, Swift, Kotlin, Scala, R, MATLAB, Bash/Shell scripting, PowerShell, Groovy, Elixir, Clojure, Haskell, Dart, Objective-C, COBOL (legacy systems), FORTRAN (scientific computing), Perl, Lua, Julia
React, React Native, Next.js, Vue.js, Nuxt.js, Angular, Svelte, SvelteKit, Remix, Astro, HTML5, CSS3, Sass/SCSS, Tailwind CSS, Bootstrap, Material UI, Storybook, WebSockets, WebAssembly (WASM), Progressive Web Apps (PWA), Web Components, Vite, Webpack, Rollup, Babel, ESLint, Prettier, Jest, Cypress, Playwright, Testing Library
Node.js, Express.js, FastAPI, Django, Flask, Spring Boot, ASP.NET Core, Ruby on Rails, Laravel, Gin (Go), Fiber (Go), gRPC, GraphQL, REST API design, OpenAPI/Swagger, Websocket server, message queues (RabbitMQ, SQS), background jobs, rate limiting, API versioning, OAuth 2.0, JWT, SAML, microservices, monolith, serverless functions
PostgreSQL, MySQL, Microsoft SQL Server, Oracle Database, SQLite, MongoDB, DynamoDB, Cassandra, Redis, Memcached, Elasticsearch, OpenSearch, Neo4j (graph database), InfluxDB (time-series), CockroachDB, PlanetScale, Supabase, Firebase Realtime Database, Firestore, Snowflake, BigQuery, Redshift, Databricks, dbt (data build tool), Apache Iceberg, Delta Lake, Parquet, Avro
Amazon Web Services (AWS), Microsoft Azure, Google Cloud Platform (GCP), AWS EC2, AWS Lambda, AWS S3, AWS RDS, AWS EKS, AWS ECS, AWS CloudFormation, AWS CDK, Azure Functions, Azure Kubernetes Service (AKS), Azure DevOps, Google Kubernetes Engine (GKE), Google Cloud Run, Google Cloud Functions, multi-cloud strategy, hybrid cloud, FinOps, cloud cost optimisation, reserved instances, spot instances
Docker, Kubernetes, Helm, Kustomize, ArgoCD, Flux, Terraform, Pulumi, Ansible, Chef, Puppet, Jenkins, GitHub Actions, GitLab CI/CD, CircleCI, Travis CI, Bitbucket Pipelines, Tekton, Spinnaker, blue-green deployment, canary releases, feature flags, trunk-based development, GitOps, infrastructure as code (IaC), site reliability engineering (SRE), chaos engineering, incident management, runbooks, postmortem culture, SLO/SLA/SLI, error budgets
TensorFlow, PyTorch, scikit-learn, XGBoost, LightGBM, Keras, Hugging Face Transformers, LangChain, LlamaIndex, OpenAI API, Anthropic Claude API, Pandas, NumPy, SciPy, Matplotlib, Seaborn, Plotly, Jupyter Notebook, Apache Spark, PySpark, MLflow, DVC (Data Version Control), Weights & Biases, feature engineering, model training, hyperparameter tuning, cross-validation, A/B testing, statistical significance, p-value, confidence intervals, regression analysis, classification, clustering, NLP (Natural Language Processing), computer vision, RAG (Retrieval-Augmented Generation), fine-tuning, prompt engineering, vector embeddings, Pinecone, Weaviate, Chroma, FAISS
penetration testing, vulnerability assessment, OWASP Top 10, SAST (Static Application Security Testing), DAST (Dynamic Application Security Testing), SIEM (Security Information and Event Management), Splunk, Microsoft Sentinel, IBM QRadar, EDR (Endpoint Detection and Response), CrowdStrike, SentinelOne, zero-trust architecture, SASE (Secure Access Service Edge), identity and access management (IAM), privileged access management (PAM), public key infrastructure (PKI), SSL/TLS, certificate management, secrets management, HashiCorp Vault, AWS Secrets Manager, SOC 2, ISO 27001, HIPAA compliance, PCI DSS, NIST CSF, MITRE ATT&CK, threat modelling, incident response, forensics, CISSP, CISM, CEH, OSCP, CompTIA Security+
Agile methodology, Scrum, Kanban, SAFe (Scaled Agile Framework), sprint planning, backlog grooming, user story mapping, OKRs (Objectives and Key Results), KPIs, product roadmap, go-to-market strategy, product-led growth (PLG), product discovery, user research, A/B testing, cohort analysis, funnel optimisation, NPS (Net Promoter Score), DAU/MAU, churn rate, LTV (Lifetime Value), CAC (Customer Acquisition Cost), SQL, data-driven product decisions, stakeholder management, cross-functional teams, JIRA, Confluence, Linear, Notion, Figma, ProductBoard, Amplitude, Mixpanel, Pendo
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