Mid-Level AI Engineer

Mid-Level AI Engineer - Application Security & AI Systems - Contract - Remote - $70.00 - $83.33/hr.

The final salary or hourly wage, as applicable, paid to each candidate/applicant for this position is ultimately dependent on a variety of factors, including, but not limited to, the candidate's/applicant's qualifications, skills, and level of experience as well as the geographical location of the position.

Applicants must be legally authorized to work in the United States. Sponsorship not available.

Our client is seeking Mid-Level AI Engineer - Application Security & AI Systems for a Remote Opportunity

Role Description

Development & Enforcement
Design, build, and maintain secure AI-powered applications, services, and intelligent automation solutions.
Develop reusable frameworks, APIs, libraries, and tooling that accelerate AI adoption across engineering teams.
Implement security controls and automated guardrails directly into development workflows, CI/CD pipelines, and AI-assisted engineering environments.
Conduct secure code reviews and provide remediation guidance for applications developed in Python, Go, Rust, JavaScript, and related technologies.
Establish and promote secure coding standards, security requirements, and responsible AI engineering practices.
Support DevSecOps initiatives by integrating application security controls throughout the software development lifecycle.
Collaboration & Expertise
Partner with engineering, architecture, product, security, and operations teams to design and deliver secure AI-enabled solutions.
Provide technical expertise on AI application development, software security, and cloud-native architectures.
Participate in architecture reviews, design sessions, and technical planning activities.
Collaborate with developers to embed security best practices into applications and engineering workflows.
Support enterprise AI adoption initiatives through guidance, consultation, and engineering leadership.
Analysis & Configuration
Conduct application security assessments, vulnerability analysis, and remediation planning.
Evaluate AI systems and workflows for risks including prompt injection, data leakage, model abuse, and unauthorized access.
Participate in threat modeling exercises across distributed systems, cloud-native environments, and AI-enabled applications.
Analyze and configure security controls across cloud, hybrid, and on-premises environments.
Document findings, technical recommendations, standards, and operational procedures.
Operational Support
Support production AI systems, applications, and security platforms to ensure reliability and security.
Troubleshoot and resolve application security issues, platform vulnerabilities, and operational challenges.
Assist with incident response activities involving application security events, AI misuse, or data protection concerns.
Monitor system performance, security posture, and operational metrics.
Contribute to ongoing platform maintenance, optimization, and continuous improvement initiatives.
Participate in on-call rotations and provide support during occasional after-hours deployments, production incidents, maintenance windows, and critical operational events as required.

Skills & Requirements

5-7 years of professional software engineering experience developing, deploying, and supporting enterprise applications.
2+ years of hands-on experience with AI technologies, including LLMs, AI agents, generative AI applications, RAG architectures, or AI-powered automation solutions.
Bachelor's degree in Computer Science, Cybersecurity, Information Systems, Software Engineering, or a related technical discipline, or equivalent practical experience.
Strong programming experience in Python, Go, Rust, JavaScript, or similar development languages.
Experience with cloud-native development, APIs, containers, Kubernetes, CI/CD pipelines, and Git-based development workflows.
Solid understanding of secure coding principles, application security fundamentals, and common vulnerability classes.
Strong analytical, troubleshooting, and problem-solving skills.
Excellent written and verbal communication skills with the ability to work effectively across technical and business teams.
Ability and willingness to work a flexible schedule, including occasional late-night deployments, production support activities, incident response efforts, maintenance events, and on-call responsibilities as business needs require.
Demonstrated ability to rapidly learn, adopt, and effectively utilize new technologies, tools, frameworks, and platforms in a fast-paced engineering environment.
Strong commitment to continuous lea