Software Engineer – AI Development

Contrast Security

. 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.

Posted 3/5/2026full-timeBaltimore • Maryland • 🇺🇸 United StatesMid-LevelSenior💰 $120,000 - $150,000 per yearWebsite

Tech Stack

Tools & technologies

AWSAzureCloudCyber SecurityDockerGoogle Cloud PlatformJavaKubernetesPythonPyTorchScikit-LearnTensorflow

About the role

Key responsibilities & impact

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

What you’ll need

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

Comp & perks

Offers Equity 📊 Check your resume score for this job Improve your chances of getting an interview by checking your resume score before you apply. Check Resume Score

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 & Tools

PythonJavaMachine LearningTensorFlowPyTorchscikit-learnGenerative AILarge Language ModelsMLOpsApplication Security

Soft Skills

MentoringCode ReviewsCollaborationProblem SolvingStaying Current with Research

Certifications

Bachelor's Degree in Computer Science