Senior QA Automation (AI-Native Testing)

We are Techbar — a tech services company led by seasoned delivery professionals and engineers.

We help startups, product companies, and digital businesses build and scale software teams through staff augmentation, dedicated squads, and full-cycle product delivery.

We are currently looking for a Senior QA Automation Engineer for a client engagement.

About the company

We're a Spec-Driven Development platform that turns specifications into working software with AI at the core. We're building the tooling and workflows that let teams ship faster without sacrificing quality — and we hold ourselves to that same bar. Our QA function isn't an afterthought; it's an AI-native discipline where engineers use LLMs and agents as first-class tools to design, generate, and evaluate tests.

Role Overview

We're looking for a Senior QA Automation Engineer to own quality across the platform and set the standard for how AI-native testing is done here. You'll write robust Playwright suites in TypeScript, orchestrate AI agents to produce test artifacts at scale, and define the evaluation strategy for our LLM-driven features. Beyond testing the platform itself, you'll use it to validate third-party applications — giving you a rare dual vantage point as both builder and power user.

As a senior member of the team, you'll do more than execute: you'll shape test strategy, raise the quality bar, mentor others, and influence how quality is engineered across the product. You should be able to operate with a high degree of autonomy and turn ambiguous quality problems into clear, durable systems. 

English: at least Upper-intermediate.

Responsibilities

• Own quality for the platform - define and drive the test strategy for the spec-driven development experience, end-to-end, from spec ingestion through generated output.
• Scale test creation with AI agents — build repeatable workflows using Claude Code, Skills, Agents, and Prompts to author, scaffold, and maintain test artifacts; establish patterns the rest of the team adopts.
• Architect API test suites - design reliable, well-structured, maintainable API automation.
• Architect UI automation - lead Playwright (TypeScript) end-to-end and component testing, including framework design and best practices.
• Direct exploratory and manual testing - cover what automation can't, and convert findings into durable automated coverage.
• Own pipelines and reporting - keep test pipelines fast, green, and trustworthy; define coverage strategy and produce reporting that leadership can act on.
• Define LLM evaluation - design and own evaluations of AI-generated output using structured evaluation frameworks, establishing what "correct" means for non-deterministic systems.
• Validate third-party apps with the platform — dogfood it against real external applications and feed insight back to the product team.
• Mentor and raise the bar - set standards, review others' test work, and grow the team's AI-native testing capability.

Requirements

• 5+ years in QA automation/test engineering, with a track record of owning quality for complex products.
• Deep TypeScript and Playwright expertise (UI and API), including framework and architecture decisions.
• Strong test design fundamentals — clear cases, meaningful assertions, zero tolerance for flakiness, honest reporting.
• Proven experience designing and maintaining CI test pipelines, coverage strategy, and reporting.
• Hands-on experience using LLMs and AI agents in real workflows — and the judgment to know where they help and where they don't.
• Experience with LLM response evaluation and evaluation frameworks for non-deterministic outputs.
• Demonstrated autonomy, ownership, and the ability to mentor and influence beyond your own work.

Nice to have:

• Hands-on Claude Code and agent-based tooling experience (Skills / Agents / Prompts).
• Experience testing AI-powered or spec-driven products.
• Track record of standing up a quality function or strategy from scratch.

Why Join

• Work at the frontier of AI-native quality engineering - redefining testing workflows, not bolting AI onto old ones.
• Real ownership and influence over how quality is engineered on a platform that changes how software is built.
• Direct impact on a product you'll use every day.