GenAI QA Engineer

Role: Gen AI QA
location: San Francisco, CA (hybrid onsite)
Duration: Long Term

 Architect, build, maintain, and improve end-to-end SDLC – AI Agents

• Implement end-to-end solutions for automated testing, performance testing and A/B testing
• Collaborate with Product,PMO, Engineering, and DevOps on planning new capabilities
• Establish scalable, efficient, automated processes for data analysis, model development, validation, and implementation
• Write efficient and well-organized software to ship products in an iterative, continual-release environment
• Actively participate in code review and test solutions to ensure it meet best practice specifications
• Write efficient and well-organized software in an iterative, continual-release environment
• Actively participate in code review and test solutions to ensure it meets best practice specifications.
• Contribute to and promote good software engineering practices across the team
• Excellent communication skills, with the ability to explain complex technical concepts to technical and non-technical audiences

 Responsibilities:

• Provide hands-on technical expertise, guidance, and mentorship to develop Agentic AI driven quality solutions, across multiple SDLC phases. Design and implement AI agents to autonomously analyze requirements, generate code, generate test scenarios, create/maintain automated test scripts, and identify gaps, risks and potential defects early in the cycle.
• Partner with DevOps and SRE teams to integrate AI-driven quality checks into CI/CD pipelines. Develop AI agents for code reviews, security scans, performance optimization and monitor production environments for anomaly detection and self-healing recommendations.
• Lead innovation pilots and POCs, evaluating emerging AI/ML tools, and recommend scalable adoption strategies. Establish and maintain MLOps practices for the AI lifecycle (model training, deployment, monitoring, and governance) and automate processes across the engineering pipeline. Coach and mentor technical teams on leveraging Gen AI and Agentic AI for productivity and quality improvements.

 We're excited about you if you have:

• 10 years of experience in the Software engineering space
• 3+ years of proven experience applying AI/ML or GenAI solutions to Develop workflows
• Deep understanding of LLM models, Agentic AI concepts (LLM orchestration, autonomous agents, RAG, prompt engineering, vector DBs), and AI/ML toolkits to solve quality engineering challenges
• Experience working with a variety of relational SQL and NoSQL databases
• Experience working with: Hadoop, Spark, Kafka, Scala, Python, etc.
• Knowledge of cloud platforms, Experience with Azure, AWS or equivalent cloud platforms
• Hands-on Experience working with Databricks
• Experience with deep learning frameworks such as PyTorch, TensorFlow, Keras or similar
• Experience with object-oriented/object function scripting languages: Python, Java, C++, Scala, etc.
• Industry experiences building and productionizing creative end-to-end Machine Learning systems
• Experience with building and operationalizing a feature
• Experience working with distributed systems, service-oriented architectures, and designing APIs/ API Graph.
• Experience using opensource LLMs
• Knowledge of data pipeline and workflow management tools
• Expert in standard software engineering methodology, e.g. Functional testing, test automation, continuous integration, defect root cause analysis, code reviews, and design documentation
• Excellent communication and interpersonal skills, including the ability to work effectively with technical and non-technical staff
• Strong leadership and stakeholder management skills.