Job DescriptionThe
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 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.
BENEFITS OF WORKING FOR HONEYWELLIn 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
ResponsibilitiesKey ResponsibilitiesAdvanced 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.
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 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.
QualificationsBasic Qualifications
- 5+ years of professional software engineering experience.
- 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.
Preferred Qualifications- Master's or Bachelor's degree in Computer Science, Software Engineering, Data Science, or a related technical field.
- 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 edge inference runtimes).
- Exposure to MLOps practices, including experiment tracking, model versioning, and automated deployment pipelines.
- Experience with cloud-based AI platforms (e.g., Azure ML, Databricks, Vertex AI, or equivalent).
