Senior Quality Engineer

Cyber Security

Artic Wolf

India, Karnataka, Bengaluru
Full-time

Strong experience with test automation and CI/CD pipelines, including building and maintaining automation frameworks.
Experience deploying services on cloud platforms such as Amazon Web Services, Microsoft Azure, or Google Cloud Platform.
Strong expertise with tools for functional, load, and fuzz testing such as Selenium, Playwright, Locust, and CATS.
Experience working with distributed systems, microservices architectures, Docker, and Kubernetes.
Experience with AI/ML testing, including validating LLM behavior, prompt‑response quality, hallucination detection, and evaluation metrics such as accuracy, latency, bias, and toxicity.
Familiarity with AI frameworks and tooling such as LangChain, LLM evaluation frameworks (e.g., Ragas), and AWS Bedrock and related AWS services (Lambda, SQS, S3).
Strong programming and problem‑solving skills in modern software engineering environments, with experience on Linux and working with APIs, OpenAPI, and relational databases such as PostgreSQL.
Passion for improving software quality through automation, testing, and continuous improvement.

Job Description

The Senior Quality Engineer – AI Integrations contributes to Arctic Wolf’s engineering organization by building scalable automation frameworks and quality solutions for artificial intelligence, machine learning, and cybersecurity applications. This role focuses on ensuring reliability, performance, and quality across distributed systems, cloud‑native services, and large language model–driven applications by creating and extending software frameworks and tools to execute, monitor, and report on automated tests, and by building and maintaining CI/CD‑integrated automation pipelines. Responsibilities include reviewing test strategies and plans, architecting automation for API validation, performance and load testing, fuzz testing, developing and maintaining testing frameworks for generative AI and ML applications, validating model behavior and prompt‑response consistency (including hallucination detection and regression testing), and implementing evaluation pipelines to measure LLM accuracy, latency, bias, toxicity, and reliability. The engineer collaborates with highly skilled software engineering teams to continuously improve engineering quality, automation practices, and testing methodologies, while learning and adopting emerging technologies in AI, cybersecurity, and cloud engineering.

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More Details

Job Category:Cyber Security
Experience Level:Senior Level
Education Level:Bachelor Degree, Master's Degree
Date Posted:05/28/2026
Closing Date:09/28/2026

About Company

Artic Wolf

The Aurora® Superintelligence Platform is engineered to deliver scalable and automated threat detection, response, and remediation capabilities to over 10,000 organizations worldwide.