Advanced Industrial Software Engineer

Advanced Software Engineer

The Advanced Software Engineer – is a senior technical contributor responsible for designing, developing, and maintaining high‑quality, scalable software solutions that leverage modern software engineering practices with AI‑enabled capabilities. This position focuses on software development of industrial process controls software using AI technology.

This role goes beyond traditional software development by integrating AI‑assisted workflows, machine learning models, and GenAI technologies into Honeywell software products, platforms, and engineering processes. The engineer will work across the full software lifecycle: requirement, architecture, design, implementation, testing, deployment, and operational support while collaborating with cross‑functional teams to deliver reliable, secure, and maintainable systems used in mission‑critical environments.

This position is based in Fort Washington PA.

Advanced Software Engineering

• Design, develop, test, and maintain complex software systems using modern programming languages, frameworks, and architectural patterns.
• Own features or subsystems end‑to‑end, from requirements and design through deployment and long‑term support.
• Apply disciplined software development practices including version control, code reviews, automated testing, and documentation.
• Ensure software meets Honeywell standards for quality, reliability, performance, cybersecurity, and safety where applicable.
• Diagnose and resolve complex technical issues in development and production environments.

AI‑Enabled Software Development

• Integrate AI‑driven capabilities into software products and internal engineering tools to improve functionality, productivity, and decision‑making.
• Apply AI techniques for use cases such as intelligent automation, anomaly detection, predictive insights, natural‑language interfaces, and engineering workflow acceleration.
• Collaborate with data scientists and platform teams to incorporate machine learning or GenAI components into production‑grade software systems.

GenAI & Applied AI Usage

• Identify and evaluate high‑value opportunities to apply GenAI within software products and engineering processes.
• Use GenAI tools responsibly to assist with code generation, documentation, test creation, debugging, analysis, and summarization.
• Design software interfaces and workflows that safely and effectively consume AI model outputs.
• Validate AI‑assisted outputs to ensure correctness, robustness, and alignment with Honeywell standards.

Technical Leadership & Collaboration

• Act as a technical mentor for less‑experienced engineers and contribute to team engineering best practices.
• Participate in architecture and design reviews, providing guidance on scalability, maintainability, and AI integration.
• Work closely with systems, hardware, cybersecurity, product management, and test teams across Honeywell.

YOU MUST HAVE

• Bachelor's degree in Computer Science, Software Engineering, Data Science, or a related technical field.
• Minimum of 5 years of professional software engineering experience in the industrial field.
• Prior experience integrating AI or data‑driven components into software products.
• Strong proficiency in one or more modern programming languages or frameworks (e.g., C++, C#, Java, Python, or modern web technologies such as HTML/React).
• Experience building and maintaining production‑grade software systems, including containerized and orchestrated environments using Docker and Kubernetes.

WE VALUE

• Experience in industrial, embedded, real‑time, or mission‑critical software environments.
• Familiarity with cloud platforms, distributed systems, or microservices architectures.
• Experience with machine learning fundamentals, including model types, evaluation metrics, and data considerations.
• Familiarity with Generative AI concepts, such as large language models (LLMs), small language models (SLMs), embeddings, prompt engineering, and retrieval‑augmented generation (RAG).
• Experience working with high‑performance artificial intelligence technologies, including leading commercial and open‑source models and inference frameworks (e.g., LLMs, vision models, local or…