Internal Developer Tools Software Engineer Jobs in Philadelphia, PA

The Advanced Software Engineer - is a senior technical contributor responsible for designing, developing, and maintaining highquality, scalable software solutions that leverage modern software engineering practices with AIenabled capabilities.

This role goes beyond traditional software development by integrating AIassisted 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 crossfunctional teams to deliver reliable, secure, and maintainable systems used in missioncritical environments.

This position is based in Fort Washington PA.

BENEFITS OF WORKING FOR HONEYWELL

In addition to a competitive salary, leading-edge work, and developing solutions side-by-side with dedicated experts in their fields, Honeywell employees are eligible for a comprehensive benefits package. This package includes employer subsidized Medical, Dental, Vision, and Life Insurance; Short-Term and Long-Term Disability; 401(k) match, Flexible Spending Accounts, Health Savings Accounts, EAP, and Educational Assistance; Parental Leave, Paid Time Off (for vacation, personal business, sick time, and parental leave), and 12 Paid Holidays .For more Honeywell Benefits information visit: https://benefits.honeywell.com/

The application period for the job is estimated to be 40 days from the job posting date; however, this may be shortened or extended depending on business needs and the availability of qualified candidates

Job Posting Date: 04/08/2026

Basic Qualifications

• 5+ years of professional software engineering experience.
• Prior experience integrating AI or datadriven 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 productiongrade software systems, including containerized and orchestrated environments using Docker and Kubernetes.

Preferred Qualifications

• Master's or Bachelor's degree in Computer Science, Software Engineering, Data Science, or a related technical field.
• Experience in industrial, embedded, realtime, or missioncritical 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 retrievalaugmented generation (RAG).
• Experience working with highperformance artificial intelligence technologies, including leading commercial and opensource models and inference frameworks (e.g., LLMs, vision models, local or edge inference runtimes).
• Exposure to MLOps practices, including experiment tracking, model versioning, and automated deployment pipelines.
• Experience with cloudbased AI platforms (e.g., Azure ML, Databricks, Vertex AI, or equivalent).

Key Responsibilities

Advanced Software Engineering

• Design, develop, test, and maintain complex software systems using modern programming languages, frameworks, and architectural patterns.
• Own features or subsystems endtoend, from requirements and design through deployment and longterm 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.

AIEnabled Software Development

• Integrate AIdriven capabilities into software products and internal engineering tools to improve functionality, productivity, and decisionmaking.
• Apply AI techniques for use cases such as intelligent automation, anomaly detection, predictive insights, naturallanguage interfaces, and engineering workflow acceleration.
• Collaborate with data scientists and platform teams to incorporate machine learning or GenAI components into productiongrade software systems.

GenAI & Applied AI Usage

• Identify and evaluate highvalue 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 AIassisted outputs to ensure correctness, robustness, and alignment with Honeywell standards.

Model Integration & MLOps

• Integrate trained ML models into applications or services using APIs or embedded inference.
• Participate in or support model lifecycle workflows including training, validation, deployment, and monitoring in collaboration with AI/ML teams.
• Apply MLOps principles such as CI/CD for models, versioning, environment promotion, and observability.

Technical Leadership & Collaboration

• Act as a technical mentor for lessexperienced 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.