The results show a clear shift towards AI integration, robust cloud infrastructure, and data processing capabilities.

1. Python is Eating the World (Again)

Python has been popular for years, but the AI boom has cemented its position as the undisputed king of startup tech stacks. Out of 3,132 jobs, Python was explicitly required in 616 of them.

Whether you're building backend services, training models, or writing data pipelines, Python is the lingua franca of the modern startup.

2. The Cloud Infrastructure Trinity: AWS, Kubernetes, GCP

Startups are no longer building their own data centers. They are relying heavily on managed cloud services and container orchestration.

  • AWS: Still the dominant cloud provider, mentioned in 410 jobs.
  • Kubernetes: The standard for container orchestration (217 jobs).
  • GCP: A strong second choice, especially for data-heavy and AI startups (210 jobs).

3. The Rise of the "AI Engineer" (LLMs)

Perhaps the most significant trend is the explicit demand for "LLM" experience. 252 jobs specifically asked for experience working with Large Language Models. This isn't just for researchers; startups need engineers who can integrate APIs from OpenAI or Anthropic, manage vector databases, and build RAG (Retrieval-Augmented Generation) pipelines.

4. The Data Stack: Spark, Databricks, Snowflake

As companies collect more data to feed their AI models, the demand for robust data engineering tools has skyrocketed.

  • Spark: 168 jobs
  • Databricks: 110 jobs
  • Snowflake: 93 jobs
  • dbt: 87 jobs

5. The Frontend: React and TypeScript

While backend and data roles dominate the top spots, the frontend ecosystem has largely consolidated around React (160 jobs) and TypeScript (122 jobs). If you're building user interfaces in 2026, this is the stack you need to know.

The Top 10 Most Requested Technologies

  1. Python (616)
  2. AWS (410)
  3. Salesforce (342)
  4. LLMs (252)
  5. Kubernetes (217)
  6. GCP (210)
  7. Java (195)
  8. Azure (186)
  9. Spark (168)
  10. React (160)
"The most valuable engineers in 2026 are 'T-shaped'—they have deep expertise in one area (like backend or frontend) but are broad enough to wire up an LLM API and deploy their code to Kubernetes."