We are seeking an experienced and talented AI QE Engineer to join our team. In this role, you will be responsible for validating cutting-edge artificial intelligence solutions across various domains, including generative AI, conversational AI, and predictive AI.
The application, hosted in AWS, includes EC2, S3, Lambda, Athena, DymanoDB, OpenSearch, CloudWatch, GLUE, Bedrock, SageMaker, Kendra, Amazon Q, Claude from Anthropic Titan Embeddings from in AWS, Python, Langchain, and Streamlit technologies.
Duties & Responsibilities- Experience in testing and validating AI/ML solutions including Generative AI, Conversational AI, and Predictive models
- Strong understanding of how ML models are built end-to-end (data preparation, feature engineering, training, validation, tuning)
- Knowledge of core ML algorithms and model types (regression, classification, clustering, tree-based models, neural networks, transformers)
- Proficiency in Python for AI test automation, data analysis, and model output validation
- Hands-on experience with pandas, NumPy, and scikit-learn for data and model validation
- Experience in data quality analysis, profiling, and feature validation
- Understanding of model evaluation metrics and validation of performance results
- Ability to interpret model behavior and explainability outputs
- Experience testing AI APIs and services built using FastAPI or Flask
- Familiarity with cloud-based AI deployments, preferably AWS SageMaker
- Understanding of production ML lifecycle, including deployment validation and monitoring
- Strong analytical, problem-solving, and communication skills for cross-functional collaboration
Desirable:
- Hands-on experience testing Generative AI prompts, hallucinations, and response quality
- Familiarity with Responsible AI, bias, fairness, and safety validation
- Knowledge of MLOps pipelines and CI/CD validation for ML systems Experience with performance, latency, and scalability testing for AI services
- Exposure to adversarial testing and edge-case validation for AI models
- Experience testing AI systems in regulated or high-risk domains
Skills Required
- Bachelor’s degree (B.E.) from four-year college or university, or equivalent combination of education and experience.
- 9+ years of experience in deploying and testing AI solutions, particularly in the areas of generative AI, conversational AI, and predictive AI.
- Strong proficiency in Python and experience with AI/ML libraries such as PyTorch, NumPy, scikit-learn, TensorFlow, and Keras
- Familiarity with LangChain and other NLP frameworks for building conversational agents and language models
Skills Required
- Bachelor’s degree in engineering from a four-year college or university, or equivalent education and experience
- 9+ years of experience deploying and testing AI solutions
- Experience testing generative AI, conversational AI, and predictive AI solutions
- Strong proficiency in Python
- Experience with PyTorch, NumPy, scikit-learn, TensorFlow, and Keras
- Familiarity with LangChain and other NLP frameworks for conversational agents and language models
- Experience with data quality analysis, profiling, and feature validation
- Experience testing AI APIs and services built with FastAPI or Flask
- Familiarity with cloud-based AI deployments, preferably AWS SageMaker
- Understanding of machine learning model development, evaluation metrics, explainability, deployment validation, and monitoring
- Hands-on experience testing generative AI prompts, hallucinations, and response quality
- Familiarity with responsible AI, bias, fairness, and safety validation
- Knowledge of MLOps pipelines and CI/CD validation for machine learning systems
- Experience with performance, latency, and scalability testing for AI services
- Exposure to adversarial testing and edge-case validation for AI models
- Experience testing AI systems in regulated or high-risk domains
What We Do
Better operations. Better outcomes. As the leader in healthcare operations solutions, anchored in governance, risk management, and compliance, symplr enables enterprise customers to efficiently navigate the unique complexities of integrating critical business operations in healthcare. Our healthcare-specific software solutions and professional services provide value far beyond single, siloed solutions and enhance customers’ ability to achieve truly connected, integrated, enterprise-wide operational efficiencies. For over 30 years, healthcare organizations have trusted our expertise and depended on our provider data management, workforce and talent management, contract management, spend management, access management, and compliance, quality, safety solutions to help drive better operations for better outcomes.
