Hybrid Software Engineer – AI Development

at Contrast Security

• Job title: Software Engineer – AI Development
• Job type: Full Time
• Experience level: Mid level, Senior
• Salary: $120,000 - $150,000 per year
• Degree requirement: Bachelor's Degree
• Tech skills: AWS, Azure, Cloud, Cyber Security, Docker, Google Cloud Platform, Java, Kubernetes, Python, PyTorch, Scikit-Learn, Tensorflow
• Location requirements: Hybrid, Baltimore, United States

About the role

• Software Engineer tasked with designing and deploying AI/ML solutions for enhancing application security. Working at Contrast Security, focusing on innovative cybersecurity measures.

Responsibilities

• Design, build, and deploy production-grade AI/ML systems to solve complex security problems, from traditional vulnerability detection models to LLM-powered code analysis and remediation agents.
• Design and implement advanced prompt engineering strategies and build complex, multi-step agentic workflows to power our intelligent features.
• Build and optimize the data pipelines, training workflows, and serving infrastructure that form the backbone of our AI platform.
• Partner closely with engineering teams and security researchers to integrate AI/ML models into the Contrast platform and solve real-world customer problems.
• Contribute to our engineering culture by participating in code reviews, mentoring team members, and staying current with the latest research in AI and cybersecurity.

Requirements

• 4+ years of professional software engineering experience building and deploying production systems.
• Expertise in Python and common AI/ML frameworks.
• Proficiency in Java for building and maintaining production-grade backend services.
• Demonstrable experience in one or both of the following areas:
• A) Machine Learning: Hands-on experience building, training, and deploying ML models in production using frameworks like TensorFlow, PyTorch, or scikit-learn.
• B) Generative AI: Experience developing applications using Large Language Models (LLMs), including prompt engineering, RAG systems, or agentic frameworks.
• Experience deploying applications in a cloud environment (e.g., AWS, GCP, Azure).
• A bachelor's degree in Computer Science, a related technical field, or equivalent practical experience.
• A strong understanding of application security concepts and vulnerability types (preferred).
• Experience with MLOps tools and practices (e.g., Docker, Kubernetes, CI/CD) (preferred).
• Experience using AI coding assistants (e.g., GitHub Copilot, Claude Code) as part of your professional workflow (preferred).

Benefits

• Offers Equity