SDET (AI & Next-Gen Automation)

Capgemini•Atlanta, GA

1d•$53,580 - $122,400•Onsite

About The Position

We are looking for a Software Development Engineer in Test (SDET) to join our next-gen Quality Engineering team. This role is ideal for engineers who go beyond traditional automation and actively experiment with LLMs, agentic workflows, and AI-assisted testing to solve complex quality challenges. You will help build intelligent, self-evolving test systems that leverage generative AI, prompt engineering, and autonomous agents to transform how software quality is validated at scale.

Requirements

1–5 years of experience in test automation, with strong coding skills and a passion for innovation.
Proficiency in at least one programming language such as Python (preferred), Java, or JavaScript.
Hands-on experience with modern automation frameworks (Selenium, Playwright, Cypress, or similar with MCP).
Proven interest in AI-driven testing, demonstrated through projects, GitHub contributions, research, or coursework.
Practical exposure to LLMs (e.g., OpenAI, Azure OpenAI, Hugging Face), including prompt engineering or API-based integrations.
Experience with API testing and service validation (Postman, RestAssured, or similar tools).
Understanding of CI/CD pipelines, DevOps practices, and version control (Git).
Strong analytical mindset with the ability to experiment, prototype, and rapidly learn new technologies.

Nice To Haves

You actively build side projects or contribute to open-source in automation or AI testing.
You are curious about how LLMs can replace or augment traditional QA practices.
You think in terms of systems, not just test cases—focusing on scalability, intelligence, and efficiency.
You are comfortable working in fast-evolving, ambiguous problem spaces and enjoy pushing boundaries.
Familiarity with agentic or orchestration frameworks (LangChain, AutoGPT, Semantic Kernel, etc.) is strongly preferred.
Working knowledge of cloud platforms (AWS, Azure, or GCP) and containerization (Docker) is a plus.

Responsibilities

Design and build AI-powered test automation solutions, including prompt-driven and LLM-assisted validation workflows.
Develop and enhance automation frameworks across UI, API, and distributed systems, with a focus on scalability and reusability.
Build self-healing and adaptive test solutions using AI techniques (e.g., dynamic locators, test generation, anomaly detection).
Experiment with and integrate agentic frameworks (LangChain, Semantic Kernel, AutoGPT, etc.) for autonomous test execution and orchestration.
Contribute to test generation using LLMs—converting requirements, user stories, or logs into executable test cases.
Integrate AI-driven testing into CI/CD pipelines to enable continuous, intelligent quality validation.
Collaborate closely with developers, DevOps, and AI/ML engineers to embed testing early in the development lifecycle.
Analyze failures using logs, telemetry, and AI-assisted debugging techniques to accelerate root cause identification.