Senior Engineer, AI Code Modernization

About the role

Location: Hybrid – Exton, PA/Philadelphia

Bentley is building a specialized AI Code Modernization team focused on applying advanced AI techniques to transform large-scale engineering software systems. This team is responsible for developing AI-powered modernization pipelines that help migrate and evolve complex legacy applications, including scientific and engineering codebases, into modern cloud-native architectures. This is a highly applied engineering role. You will work at the intersection of software engineering, AI systems, developer tooling, and modernization automation. Success is measured through production impact, scalability, reliability, and the ability to accelerate modernization across Bentley's portfolio of products.

Responsibilities

• Design and build AI-driven software transformation pipelines for large-scale legacy codebases.
• Develop and improve agentic AI workflows that support code understanding, refactoring, validation, and modernization.
• Modernize existing desktops, simulation, and engineering applications into cloud-native services and modern architectures.
• Use loop engineering approach to improve quality, reduce costs and accelerate the conversion/test/correction process.
• Evaluate and improve AI systems for accuracy, reliability, performance, observability, and cost efficiency.
• Create automated tooling, validation frameworks, and testing strategies to ensure correctness of transformed code.
• Partner with architects, product leaders, and engineering teams to identify modernization opportunities and drive adoption.
• Contribute to technical direction, best practices, and reusable modernization frameworks that can be leveraged across Bentley.
• Help establish and share expertise in a rapidly evolving AI domain.

Requirements

• Strong software development background with ownership of production systems.
• Experience building, maintaining, or modernizing complex software applications.
• Demonstrated understanding of software performance, reliability, scalability, testing, and failure modes.
• Practical experience applying AI, machine learning, inference pipelines, optimization techniques, or intelligent automation to real-world problems.
• Systems-oriented mindset with the ability to bring structure to ambiguous technical challenges.
• Experience designing pipelines, feedback loops, iterative systems, or large-scale developer tooling.
• Strong communication skills and the ability to collaborate with technical and non-technical stakeholders.

Preferred Qualifications

• Experience with Rust, C++, C, or Fortran.
• Experience modernizing legacy systems or migrating applications to cloud-native architectures.
• Background in DevOps, CI/CD pipelines, testing frameworks, simulation systems, benchmarking, or validation tooling.
• Experience working with engineering, scientific, mathematical, or simulation software.
• Familiarity with cloud platforms and distributed systems.
• Interest in emerging AI development patterns, agentic workflows, and software transformation technologies.

What Success Looks Like

• Modernize existing systems rather than only building greenfield solutions.
• Make thoughtful tradeoffs between performance, reliability, latency, maintainability, and