Development Engineer

POSITION: Development Engineer, Monitoring & Diagnostics

• Utilize and expand AWS Cloud infrastructure to enhance data analytics and monitoring capabilities (AWS full stack development, EC2, S3, Lambda, Amplify)
• Utilize AI models for knowledge base agent/digital twin of gas turbine.
• Develop/maintain software for monitoring, analyzing and graphically representing gas turbine operations.
• Continuously refine/train models to mimic real life engine behavior, minimize false alarms, and predict gas turbine alarms before they occur
• Work with operational team to support and troubleshoot issue with customer data and cloud infrastructure
• Continuously improve the OSIsoft PI system architecture
• Other duties as assigned

• Education: Bachelor's degree in Computer Science, Data Science, Data Analytics , Mechanical Engineering, or a related quantitative/technical field .

• Generative AI & ML: Practical experience with Machine Learning (ML) and Artificial Intelligence (AI) frameworks. Familiarity with Large Language Models (LLMs) and Foundational Models via platforms like Amazon Bedrock.
• Full-Stack Development: Understanding of AWS Full-Stack development workflows, including API Management, IAM roles, and cloud security best practices.
• AWS Cloud Ecosystem: Hands-on experience with AWS Cloud Architecture. Proficiency in core services including EC2 (Compute), S3 (Storage), and AWS Lambda (Serverless).
• Programming Languages: Proficiency in at least one modern language: Python, TypeScript, C#, or MATLAB.
• DevOps & Tools: Basic knowledge of Software Development Life Cycle (SDLC), Version Control (Git/GitHub), and Continuous Integration/Continuous Deployment (CI/CD) pipelines.
• Methodology: Familiarity with Agile/Scrum environments and iterative development processes.
• Data Analysis: Strong aptitude for data visualization and data modeling.
• DataBase experience: Experience with SQL and noSQL databases.

• AWS Certifications: Active certifications such as AWS Certified Developer, Solutions Architect, or Machine Learning - Specialty.
• Advanced AI/ML: Exposure to Natural Language Processing (NLP), Neural Networks, or Generative AI integration via Amazon Bedrock and SageMaker.
• Data Science Stack: Proficiency in data manipulation libraries (e.g., Pandas, NumPy, Scikit-learn)
• Modern Web Frameworks: Experience in Full-Stack Development using React.js and TypeScript to build responsive user interfaces.
• API Development: Knowledge of building and consuming RESTful APIs or GraphQL to connect front-end applications with cloud backends.
• State Management: Familiarity with tools like Redux, Context API, or Zustand for complex UI logic.
• Version Control: Mastery of Git workflows, including branching strategies, pull requests, and code reviews.
• CI/CD Pipelines: Experience with AWS CodeCommit, GitHub Actions, or GitLab CI for automated testing and deployment.
• Infrastructure as Code (IaC ): Basic understanding of AWS CloudFormation or Terraform is a significant advantage.