Senior Industrial Software Engineer

Honeywell

Senior Advanced Software Engineer at Honeywell designing and developing AI-enabled industrial process controls software. Collaborating with cross-functional teams over the software lifecycle in a hybrid work environment.

Posted 7/20/2026full-timeFort Washington • Pennsylvania, Washington • 🇺🇸 United StatesSeniorWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in designing and developing complex software systems with a strong focus on integrating AI-driven capabilities and ensuring high standards of quality and performance. Proficient in modern programming languages and frameworks, with extensive experience in production-grade software environments and machine learning fundamentals.

Highest-signal resume keywords

AI IntegrationModern Programming LanguagesProduction-Grade Software SystemsMachine Learning FundamentalsCloud-Based AI Platforms

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

C++C#JavaPythonHTMLReactDockerKubernetesMachine LearningGenerative AI

Soft Skills

Technical MentorshipCollaboration

Tools & Technologies

Azure MLDatabricksVertex AI

Industry Keywords

Industrial SoftwareEmbedded SystemsReal-Time SoftwareMission-Critical SoftwareDistributed SystemsMicroservices Architecture

Tech Stack

Tools & technologies

AzureCloudCyber SecurityDistributed SystemsDockerJavaKubernetesMicroservicesPythonReact

About the role

Key responsibilities & impact

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.
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.
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.
Act as a technical mentor for less‑experienced engineers and contribute to team engineering best practices.

Requirements

What you’ll need

Bachelor’s degree in Computer Science, Software Engineering, Data Science, or a related technical field.
Minimum of 8 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.
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).
Experience with cloud‑based AI platforms (e.g., Azure ML, Databricks, Vertex AI, or equivalent).

Benefits

Comp & perks

In addition to a performance-driven salary, cutting-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.