Senior Industrial Software Engineer

Jobtailor

Pennsylvania

On-site

USD 150,000 - 200,000

Full time

14 days+

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Job summary

Jobtailor in the United States is seeking a senior software engineer to design, develop, and maintain complex AI-enabled systems. You will own features end-to-end, integrate GenAI capabilities, and work with data scientists to push ML components into production.

You will mentor junior engineers, uphold coding standards, and ensure reliability, performance, and cybersecurity where applicable. A strong background in C++, Java, or Python and cloud AI platforms is required.

Qualifications

Bachelor’s degree in CS, Software Engineering, Data Science, or related field.
Minimum 8 years of professional software engineering experience in an industrial field.
Experience integrating AI or data-driven components into software products.
Strong proficiency in one or more modern programming languages (C++, C#, Java, Python) and modern web technologies like HTML/React.
Experience with Docker and Kubernetes in production-grade systems.
Experience in industrial, embedded, real-time, or mission-critical software environments.
Familiarity with cloud platforms, distributed systems, or microservices architectures.
Knowledge of machine learning fundamentals and Generative AI concepts.
Experience with cloud-based AI platforms such as Azure ML, Vertex AI, or equivalent.

Responsibilities

Design, develop, test, and maintain complex software systems with AI capabilities.
Own features or subsystems end-to-end from requirements to deployment.
Apply disciplined development practices including version control, testing, and documentation.
Ensure software meets quality and safety standards.
Diagnose and resolve complex technical issues in development and production.
Integrate AI-driven capabilities into products and engineering tools.
Collaborate with data scientists and platform teams to include ML/GenAI components.
Mentor less-experienced engineers and contribute to engineering best practices.

Skills

AI Integration

Machine Learning Fundamentals

Distributed Systems

Mentorship

Collaboration

Education

Bachelor's degree in Computer Science or related

Tools

Docker

Kubernetes

Azure ML

Databricks

Vertex AI

React

HTML

Python

C++

Java

Job description

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

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).

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.

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