Sr Software Engineer

Description

Brady Corporation is seeking a Senior Software Engineer to join our Applications Engineering team, building applications, our web SDK, and AI solutions for customers and internal teams. You’ll develop software across desktop, mobile, and web platforms, integrate AI agents into business and labeling workflows, and help establish the infrastructure and tools that make AI adoption practical and reliable.

You’ll combine strong software engineering skills with hands-on experience applying AI to real business problems. You’ll build and maintain our web SDK so developers can integrate Brady’s labeling capabilities into their applications, while exploring ways AI can simplify workflows and enable new capabilities.

Working with engineering, product, IT, and security teams, you’ll turn ideas into production solutions with attention to quality, security, reliability, and cost. If you enjoy building useful software and helping teams put AI to work, we’d like to hear from you.

Qualifications

• Design, develop, and maintain AI-enabled applications and automation that improve Brady’s customer experiences, labeling workflows, and internal operations.
• Build and integrate AI agents that connect models with business systems, tools, and data, using appropriate permissions, human approval steps, and recovery mechanisms.
• Help establish the infrastructure and shared tooling for AI adoption, including model access, secure system connections, development environments, deployment pipelines, and monitoring, in partnership with IT and security teams.
• Evaluate AI models and agent workflows against practical business requirements, and improve their accuracy, reliability, performance, and cost.
• Develop supporting applications, APIs, and SDK integrations using C#/.NET and TypeScript/JavaScript, working across desktop, mobile, and web platforms as projects require.
• Use AI-assisted development tools throughout implementation, testing, documentation, and troubleshooting, while maintaining ownership of software quality.
• Collaborate with product management, domain experts, and engineering teams to identify useful AI opportunities and turn prototypes into production solutions.
• Establish reusable components and practical guidance that help other teams build, deploy, and support AI solutions.