What is a tech stack? Meaning, examples, and how to find any company's stack

“Tech stack” is one of the most used phrases in software and one of the least precisely used. Engineers mean one thing by it, sales and marketing teams mean something wider, and job seekers mostly want to know what a specific company runs before they apply. This guide covers all three: what the term means, what “tech stack” means in business, real examples read from live job postings, and how to find out the tech stack of any company in two steps.

What is a tech stack?

A tech stack is the set of technologies a company uses to build and run its products: the programming languages, frameworks, databases, cloud platform, and the tools around them. It is called a stack because the pieces sit in layers, from the database and servers at the bottom to the user interface at the top, each depending on the layer beneath it.

The classic split is frontend (what runs in the browser or the app), backend (the servers and application logic), data (the databases and warehouses), and infrastructure (the cloud, containers, and the tooling that deploys and monitors everything). A typical stack names one or two technologies at each layer:

• Frontend: a framework such as React, Vue.js or Angular, usually written in TypeScript.
• Backend: a language and framework pair such as Python and Django, Java and Spring, Go, Rust, or Node.js.
• Data: a transactional database such as PostgreSQL, MySQL or MongoDB, a cache such as Redis, and increasingly a warehouse such as Snowflake or Databricks.
• Infrastructure: a cloud (AWS, Azure, Google Cloud), containers (Docker, Kubernetes), infrastructure as code (Terraform), and observability (Datadog, Splunk).
• Tooling: source control and CI (GitHub, GitLab, Jenkins), issue tracking (Jira), and design (Figma).

The word has a narrower cousin, “stack” on its own, which usually means the language-and-framework choice for one application (“a Rails stack”, “the MERN stack”). “Tech stack” is the whole picture.

What does tech stack mean in business?

In business, tech stack means every software product a company runs to operate, not only what its engineers build with. It includes the CRM, the marketing automation, the ERP and accounting system, the support desk, the BI tools, and the analytics, payment and chat vendors on the company’s website. A sales stack, a marketing stack and a data stack are all subsets of it.

That wider meaning is why the phrase shows up in job postings far outside engineering. A revenue operations posting names Salesforce and Marketo. A finance posting names NetSuite or SAP. A support posting names Zendesk or Intercom. An analyst posting names Power BI or Tableau. Each of those is a company telling you, in public, one layer of its business stack.

The business meaning is also the one that money attaches to. Software vendors sell into stacks: an integration partner wants every company on HubSpot, a migration consultancy wants every company still on Magento, a security vendor wants every company running Splunk. The data that describes which companies run which technologies is called technographics, and the tech stack is what it describes.

Examples of tech stacks

The most honest examples of tech stacks are the ones companies write themselves, in the requirements section of a job posting. JobsPipe collects postings from ten job boards and applicant tracking systems and extracts the technologies each one names into a technology_slugs field, so a posting for a backend role comes back with a stack attached, for example:

"technology_slugs": ["python", "django", "postgresql"]

Read across thousands of postings, a handful of patterns repeat. The table below names the common combinations and, for each, some of the companies with the most active postings naming its anchor technology right now.

Two things stand out from the real data. First, stacks are rarely pure: the same company often names Python for data work and TypeScript for product work, and a posting that names Kubernetes almost always names a cloud and Docker beside it. Second, the business stack and the engineering stack live in the same company but in different postings, which is why a homepage scan and a job search see different halves of it. The per-technology pages at companies using each technology list who is hiring for each one, split by industry, country and company size.

How to know the tech stack of a company

There are two public sources, and they see different halves of the stack. A website scan reads what the company serves on its public site. A job-posting search reads what its teams name when they hire. Use both and you have the whole picture in a couple of minutes.

Step 1: scan the website

Paste the domain into the free tech-stack lookup. It fetches the public site, matches scripts, headers, cookies and meta tags against a library of technology signatures, and returns the frontend framework, analytics, CDN, payment, chat and marketing tools it finds, with a confidence score for each. No signup. The same scan is one API call:

curl -X POST https://api.jobspipe.dev/v1/stack/scan \
  -H "Authorization: Bearer $JOBSPIPE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"domain": "stripe.com", "mode": "auto"}'

What a scan cannot see is anything behind login or inside the company’s own infrastructure: the cloud account, the databases, the warehouse, the CRM, the ERP, the languages the backend is written in. For those, go to the postings.

Step 2: search the company’s job postings

Search active postings by company name and read the technology_slugs on each result. Add skills_or to test a specific hypothesis, such as whether the company is hiring for Kubernetes or Snowflake:

curl -X POST https://api.jobspipe.dev/v1/jobs/search \
  -H "Authorization: Bearer $JOBSPIPE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "company_name_or": ["Stripe"],
    "skills_or": ["kubernetes", "snowflake", "python"],
    "status": "active",
    "limit": 50
  }'

Each job in the response carries technology_slugs and keyword_slugs alongside the title, seniority, location and salary where stated, so the company’s engineering stack falls out of a single query. Use company_name_partial_match_or when you are unsure of the exact registered name, and discovered_at_gte to see only what the company started hiring for recently. The same two tools are available to AI agents through the MCP server as detect_company_tech_stack and search_jobs.

One caveat worth repeating: a posting is a hiring signal, not a purchase record. A company can name a technology because it runs it, because it is migrating away from it, or because it wants candidates who know it. Read several postings and the pattern is usually unambiguous.

Why tech stacks matter for sales and recruiting

For a sales team, a company’s tech stack is the qualifier. It says whether the account fits (they run the platform you integrate with), whether it is a displacement target (they run your competitor), and, when read from postings, whether it is in motion right now (they just started hiring for the category you sell). That last part is what a website scan cannot give you, and it is the difference between a static list and a hiring signal.

For a recruiter or a sourcing product, the stack is the search. Which companies hire for Rust? Which industries hire for Salesforce administrators? Which company sizes hire for dbt? The chart below is the share of active postings that name each of the most common technologies, across the ten boards JobsPipe collects, which is the demand side of every one of those questions.

Whichever side you are on, the workflow is the same: scan the website for the public surface, search the postings for the internal stack, and let the posting date tell you when the company started caring. The technographics guide goes deeper on where each kind of stack data comes from and what each source misses.