Employment Type

Salaried, Exempt (OT Eligible)

Job Summary

The Development Engineer designs, develops, and supports monitoring and diagnostics applications for industrial gas turbines. The role focuses on AWS cloud infrastructure, data analytics, AI and Machine Learning models, and full-stack software development.

Essential Duties and Responsibilities

- Design, develop, and maintain AWS cloud infrastructure for monitoring and diagnostics applications, including EC2, S3, Lambda, and Amplify.

- Develop and support AI and Machine Learning models used for gas turbine monitoring, diagnostics, and predictive maintenance.

- Build and maintain digital twins of gas turbine assets using operational and historical data.

- Develop and maintain full-stack applications for data visualization and analysis of gas turbine performance.

- Analyze operational data to improve alarm logic, reduce false positives, and detect abnormal equipment behavior.

- Support and troubleshoot customer data pipelines, cloud services, and application issues.

- Collaborate with cross-functional engineering and operations teams using Agile development practices.

- Follow SDLC best practices, including version control, testing, and deployment.

Minimum Qualifications

- Bachelor’s degree in Computer Science, Data Science, Data Analytics, Mechanical Engineering, or a related technical field and two-three years of experience; or Masters degree in above field.

- Hands-on experience with AWS cloud services, including EC2, S3, and AWS Lambda or equivalent cloud platform experience.

- Experience with full-stack software development, including API development, IAM roles, and cloud security concepts.

- Practical experience with Artificial Intelligence (AI) and Machine Learning (ML) frameworks.

- Familiarity with Large Language Models (LLMs) or Generative AI platforms such as Amazon Bedrock.

- Proficiency in at least one programming language: Python, TypeScript, C#, or MATLAB.

- Experience with SQL and NoSQL databases.

- Working knowledge of Git, version control workflows, and the Software Development Life Cycle (SDLC).

- Experience working in Agile or Scrum development environments.

- Strong data analysis and data visualization skills.

Preferred Qualifications

- Experience with Natural Language Processing (NLP), neural networks, or Generative AI solutions.

- Experience using Amazon SageMaker for model development or deployment.

- Proficiency with data science libraries such as Pandas, NumPy, and Scikit-learn.

- Experience developing front-end applications using React.js and TypeScript.

- Experience building and consuming RESTful APIs

- Familiarity with state management tools such as Redux, Context API, or Zustand.

- Experience with CI/CD pipelines using GitHub Actions, GitLab CI, or AWS CodeCommit.

- Knowledge of Infrastructure as Code (IaC) using AWS CloudFormation or Terraform.

- Direct experience with the AVEVA PI System, including Asset Framework (AF), PI Vision, and PI System Explorer.

- AWS certifications (Developer, Solutions Architect, or Machine Learning – Specialty).

- Familiarity with Industrial Gas Turbine operation is plus.