Applications
Resources
News
Blog
Jobs
LOG IN
SIGN UP
Tech Job Finder - Find Software, Tech Sales and Product Manager Jobs.
Sign In
OR continue with e-mail and password
E-mail address
Password
Don't have an account?
Reset password
Join Tech Job Finder
OR continue with e-mail and password
E-mail address
Username
Password
Confirm Password
How did you hear about us?
By signing up, you agree to our Terms & Conditions and Privacy Policy.

Supercharge
Your SWE Career

Best-in-class toolkit to beat your competition

Asseenon

College RecruiterThe AI JournalNearshore AmericasPursue the PassionProject ManagementCollege RecruiterThe AI JournalNearshore AmericasPursue the PassionProject Management

Supercharge
Your SWE Career

Best-in-class toolkit to beat your competition

Leetcode/Algo Prep

Personalised algorithm problems. Ace progressive leetcode challenges based on your implementation skills and pass with confidence. It's not rocket science - it's just practice and recognising patterns.

Technical Quizzes

Know what you are talking about and be able to drop down from high-level discussions to low-level. Test and fix your understanding of the most important concepts and theory.

Interview Practice

Ace HireVue and automated one-way interviews with personalised feedback, which will analyze both verbal and non-verbal communication.

Latest Articles

Top 5 Use Cases for Agentic DevOps

Tech Job Finder · 20 days ago

Agentic AI represents a transformative leap in DevOps practices. Unlike traditional generative AI that produces code or suggestions on demand, agentic AI systems are autonomous agents capable of observing environments, reasoning through problems, planning multi-step actions, and executing them with minimal human intervention. These agents integrate deeply with tools like CI/CD pipelines, infrastructure-as-code (IaC), monitoring platforms, and version control systems, turning reactive operations into proactive, self-healing workflows. As of 2026, organizations adopting agentic AI in DevOps report significant gains: reduced mean time to recovery (MTTR) by up to 75%, faster deployment cycles, and engineers freed from toil to focus on strategic innovation. This article explores the best real-world use cases, drawing from tools like GitHub Copilot Agents, AWS DevOps Agent, Harness AI, and open-source frameworks.

Introduction to OpenClaw

Tech Job Finder · 20 days ago

In the rapidly evolving landscape of artificial intelligence, few projects have captured the imagination of developers, enthusiasts, and everyday users quite like OpenClaw. Launched in late 2025, this open-source autonomous AI agent has exploded in popularity, amassing hundreds of thousands of GitHub stars in record time and sparking a wave of community contributions. Often described as "the AI that actually does things," OpenClaw represents a shift from passive chatbots to proactive, task-executing personal assistants that run on your own hardware. At its core, OpenClaw is a self-hosted gateway that bridges large language models (LLMs) with real-world actions. Unlike traditional AI interfaces confined to web browsers, OpenClaw operates locally on macOS, Linux, or Windows machines. It communicates primarily through familiar messaging platforms such as WhatsApp, Telegram, Discord, Slack, Signal, and more. Users interact with it via chat, issuing commands that the agent can interpret, plan, and execute autonomously—whether that's clearing an inbox, scheduling appointments, checking flight status, or even running shell commands on the host system.

What is Databricks?

Tech Job Finder · 4 months ago

Databricks has become one of the most influential platforms in the modern data and AI landscape. As organizations grapple with exploding data volumes, the demand for real-time analytics, and the rush to deploy generative AI, Databricks stands out as a comprehensive solution that simplifies complexity while delivering enterprise-grade performance.

Latest News

Microsoft cancels Claude Code subscription because of cost concerns

Tech Job Finder · 20 days ago

In a striking reversal that underscores the unpredictable economics of generative AI, Microsoft has begun canceling internal licenses for Anthropic’s Claude Code across key engineering teams. The decision, first reported in mid-May 2026, affects thousands of developers in the company’s Experiences and Devices division — responsible for Windows, Microsoft 365, Teams, Outlook, and Surface hardware. Licenses will largely expire on June 30, 2026, the end of Microsoft’s fiscal year, with engineers directed to shift to GitHub Copilot CLI instead. What makes this move notable is not just the vendor switch but the explicit driver: runaway token costs. A tool that had become wildly popular among Microsoft’s own developers proved too expensive at scale, even for one of the world’s wealthiest technology companies. The episode highlights a growing tension in enterprise AI adoption — the gap between the promise of transformative productivity and the harsh reality of usage-based pricing.

What is Tokenmaxxing and why it won't work as a measure of productivity

Tech Job Finder · 20 days ago

In the spring of 2026, a new buzzword exploded across Silicon Valley: tokenmaxxing. At companies like Meta, engineers competed on internal leaderboards for titles such as “Token Legend” or “Session Immortal” by burning through billions of AI tokens. One top contender reportedly processed over 281 billion tokens in a single month. What started as an informal dashboard called “Claudeonomics” quickly became a cultural phenomenon — and a cautionary tale about how companies attempt to quantify productivity in the age of generative AI. Tokenmaxxing refers to the practice of deliberately maximizing the consumption of AI tokens — the basic units that large language models (LLMs) use to process and generate text — as a proxy for productivity and AI fluency. One token roughly equals four characters of text. Companies and individuals began treating high token usage as evidence of deep engagement with powerful AI tools like Claude, GPT models, or agentic workflows.

Major supply chain attack on NPM via popular Axios HTTP library

Tech Job Finder · 20 days ago

In the fast-paced world of JavaScript development, few libraries are as ubiquitous as Axios. With over 100 million weekly downloads, this promise-based HTTP client has become a cornerstone for making API requests in both browser and Node.js environments. Developers rely on it for its simplicity, interceptors, and cross-platform compatibility. But on March 31, 2026, that trust was shattered when attackers executed one of the most significant supply chain attacks in recent npm history. Malicious versions of Axios were published, silently delivering a cross-platform Remote Access Trojan (RAT) to thousands of systems.

Subscribe to Premium

GET ALL THE TOOLS YOU NEED DURING RECRUITMENT SEASON
for ONLY $19.99 50% OFF
$9.99/month

© 2026 Tech Job Finder. All Rights Reserved.
LinkedIn
Instagram
Facebook
Tech Job Finder
LinkedIn
Instagram
Facebook
© 2026 Tech Job Finder. All Rights Reserved.