Dice is the leading career destination for tech experts at every stage of their careers. Our client, Enexus Global, is seeking the following. Apply via Dice today!
Role: Gen AI QA
location: San Francisco, CA (hybrid onsite)
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.
