Engineering Manager SDET
15 hours ago
Our People With over 1,500 team members across 15+ countries, we operate in a global, remote-first environment. We are building more than software; we are building a global community rooted in creativity, collaboration, and impact. We take pride in cultivating a culture where innovation thrives, ideas are celebrated, and people come first, no matter where they call home.
Our Impact As of mid 2025, our platform powers over 1.5 billion messages, helps generate over 200 million leads, and facilitates over 20 million conversations for the more than 2 million businesses we serve each month. Behind those numbers are real people growing their companies, connecting with customers, and making their mark - and we get to help make that happen.
About the Role: We are looking for a highly skilled SDET Manager to spearhead the quality of AI application development at HighLevel. This role is very critical in ensuring the relevancy, consistency, reliability, contextual recall and fairness of our AI platform.
Ideal candidates will have a combination of technical depth in AI/ML, Agentic AI along with deep expertise in test automation covering model validation, agentic workflows, and quality leadership. Requirements:
- Overall 8-12 years of experience in which minimum of 1 year in testing AI products
- Good experience in Prompt Engineering, testing AI applications like conversations AI, voice AI, workflow AI
- Architect and scale test automation frameworks for APIs, micro-services, ML pipelines, and agentic AI workflows
- Experience in testing RAG based applications using frameworks like TruLens, RAGAs
- Leverage AI to improve coverage and efficiency across testing lifecycle
- Hands-on experience testing agentic AI frameworks (e.g., Agentic Studio, LangChain, AutoGen, crewAI)
- Strong programming skills in Python and Java or TypeScript/JavaScript
- Proven expertise in test automation frameworks (Selenium, Playwright, Cypress etc.)
- Experience with cloud platforms (AWS, GCP) and CI/CD pipelines
- Review testing strategies for AI application and fine tune strategy to minimize issues in production
- Establish evaluation pipelines for detecting hallucination, context retention, latency in multi model environments
- Generate right data set to simulate customer usage scenarios
- Test for data, model and code issues
- Define relevant KPIs for AI application testing
- Non Functional testing - Performance, Scalability, Reliability, Security
- Implement A/B testing at appropriate levels to identify customer impact
- Run down defect triaging for all customer issues to identify root cause and expand test coverage to mitigate gaps.
- Ensure quality deliverables from AI teams
- Hire top talent and mentor SDET team on AI testing skills
#LI-Remote #LI-NJ1 We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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