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Development Engineer

Power Systems Mfg., LLC
Posted 6 months ago, valid for 13 days
Location

Jupiter, FL 33468, US

Salary

Competitive

Contract type

Full Time

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Sonic Summary

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  • The position of Development Engineer, Monitoring & Diagnostics is located in Jupiter, Florida, and offers a hybrid work environment.
  • This salaried, non-exempt role requires a minimum of 3 years of experience in software development and a Bachelor's degree in a related technical field.
  • Key responsibilities include utilizing AWS Cloud infrastructure, developing software for gas turbine monitoring, and refining AI models for predictive analysis.
  • Candidates should possess proficiency in programming languages such as Python or TypeScript and have hands-on experience with AWS services like EC2 and S3.
  • The salary for this position is competitive and commensurate with experience, along with preferred skills in AI/ML frameworks and modern web development.

POSITION: Development Engineer, Monitoring & Diagnostics

LOCATION: Jupiter, Florida / Hybrid

STATUS: Salaried Non-Exempt


JOB SUMMARY

ESSENTIAL DUTIES AND RESPONSIBILITIES

The essential functions of the job include, but are not limited to, the following:

  • 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


MINIMUM REQUIREMENTS

  • 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. 

Preferred Skills/Experience

  • 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.

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