Review internal AI projects, pipelines, and architectures for security gaps, and drive mitigations.
Analyze emerging global threats and risks related to AI, and update our security policies, playbooks, and standards accordingly.
Define and refine scalable security processes and controls for AI and ML systems across their lifecycle.
Collaborate with engineers and product teams to implement secure-by-default patterns in CI/CD and MLOps workflows.
Build reference implementations and prototypes to validate security controls in real-world AI environments.
Write clear technical documentation, design diagrams, and decision records for broad consumption across engineering teams.
Act as a mentor and trusted advisor on secure engineering and AI safety topics.

Requirements

Bachelor's degree in computer science, information technology, engineering, information systems, cybersecurity, or related area and 5 years’ experience in software engineering or related area at a technology, retail, or data-driven company.
7 years’ experience in software engineering or related area at a technology, retail, or data-driven company.
Developer background with strong Python hands-on programming skills.
Experience in CI/CD and MLOps, including tools like Concord, Looper (WCNP is a bonus).
Familiarity with containerization technologies like Docker, Kubernetes, and Helm.
Strong hands-on experience with Git repositories and version control best practices.
Operational experience with hyperscale cloud platforms, particularly Azure and Google Cloud.
Comfortable in Linux environments and familiar with Infrastructure as Code (Terraform, ARM templates, or Ansible).
Understanding of workflow and rules engines and their application in security or policy enforcement.
Deep understanding of artificial intelligence concepts, frameworks (e.g., Pytorch), Generative AI and LLMs and model deployment processes (MLOps) and Hugging Face.
Knowledge of specific threats to AI/ML models, including adversarial attacks (e.g., evasion, poisoning), model inversion, and membership inference.
Demonstrated use of AI-assisted tools to boost engineering productivity and a strong grasp of Generative AI technologies, concepts and risks.

Benefits

Health benefits include medical, vision and dental coverage.
Financial benefits include 401(k), stock purchase and company-paid life insurance.
Paid time off benefits include PTO (including sick leave), parental leave, family care leave, bereavement, jury duty, and voting.
Other benefits include short-term and long-term disability, company discounts, Military Leave Pay, adoption and surrogacy expense reimbursement, and more.
Live Better U is a Walmart-paid education benefit program for full-time and part-time associates in Walmart and Sam's Club facilities.

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

PythonCI/CDMLOpsDockerKubernetesHelmGitTerraformAnsiblePytorch

Soft Skills

mentorshipcollaborationcommunicationtechnical documentationproblem-solvingadvisory