Sr. QA Analyst

Job Description:
The position is responsible for providing ongoing maintenance and support of Google Cloud Platform applications such as Document AI (DOC AI) for vital records MDHHS within our department. The DOC AI is a Google Cloud product that is used to scan paper marriage licenses, extract index information and images to FileNet and stored in a on-prem application called VERA. The application is utilized by Vital Records MDHHS employees. Changes are being made to enhance the stability and functionality of the systems. The resource is integral to developing and maintaining MDHHS DOC AI solution, streamlining critical business processes, data integrity, SEM/SUITE compliance, and securing the applications. The resource also performs as a technical lead and provides technical guidance to the other developers in the department. As a technical lead, the resource participates in a variety of analytical assignments that provide for the enhancement, integration, maintenance, and implementation of projects. The resource also provides technical oversight to developers in the team that support other critical applications. Not having a resource on staff will lead to MDHSS manually documenting and developing screen plans that can lead to errors causing data integrity issues and can eventually lead to incorrect information being processed and reporting of the patient information.

• Experience in programming languages such as Python, Java, JavaScript (Node.js), and/or C .
• Experience in Oracle/Data Bricks/Elastic/ELK.
• Proficiency in data processing and analysis using tools such as SQL, R, and/or Pandas.
• Experience in working with large datasets and data preprocessing techniques.
• Proficiency in unit testing and integration testing for chatbot flows and APIs.
• Familiarity with debugging tools and performance monitoring to ensure the chatbot runs smoothly.
• Strong understanding of conversation design and user experience principles to create intuitive and engaging chatbot interfaces.
• Ability to design, develop, and deploy AI and machine learning solutions.
• Experience with machine learning algorithms and deep learning frameworks such as TensorFlow, PyTorch, Keras, or Scikit-learn.
• Proficiency with Natural Language Processing (NLP) tools like SpaCy, NLTK, or Hugging Face's Transformers for text-based document processing.
• Knowledge of NLP concepts like intent recognition, entity extraction, and context management.
• Strong understanding of neural networks, computer vision, natural language processing, and/or reinforcement learning.
• Experience with OCR (Optical Character Recognition) Tesseract, Google Vision API, or AWS Textract.
• Proficiency in Dialogflow ES or CX, Google Assistant SDK, or other Google Cloud chatbot development tools.
• Experience in building, managing, and optimizing chatbot applications for different platforms (web, mobile, voice assistants).
• Experience in working with RESTful APIs and webhooks to enable backend communication.
• Knowledge of cloud technologies such as AWS, Google Cloud AI, or Azure AI services for document processing and AI model deployment.
• Experience with Google Cloud Platform (Google Cloud Platform), including Google Cloud Functions, App Engine, and Firestore for deploying chatbots.
• Ability to design effective conversational flows, manage dialogue context, and improve user satisfaction.
• Familiarity with agile development methodologies and version control systems like Git.
• Strong problem-solving and analytical skills with a focus on continuous improvement.
• 3 years in TensorFlow, PyTorch, Keras, or Scikit-learn.
• 3 years in microservices.
• 3 years in SpaCy, NLTK, or Hugging Face's
• 3 years in Tesseract, Google Vision API, or AWS Textract.
• 3 years in Dialogflow ES or CX, Google Assistant SDK, or other Google Cloud chatbot development tools
• 3 years in RESTful APIs and webhooks
• 3 years in SQL, R, and/or Pandas.
• 3 years in cloud computing and software development.
• 3 years software development in Python, Java, JavaScript.
• 3 years implementing core Artificial Intelligence (AI) and Machine Learning (ML) concepts.
• 3 years designing, building, and managing Google Cloud Platform (Google Cloud Platform) solutions.
• 3 years in projects development using Angular/React JS, JavaScript framework.
• 3 years programming in the JBOSS Enterprise SOA environment including JBOSS Workflow.
• 3 years using CMM/CMMI Level 3 methods and practices.
• 3 years implemented agile development processes including test driven development.
• 3 years' Experience creating CI/CD pipelines using Azure DevOps.