Work with stakeholders and business leaders to understand security needs and recommend business modifications during periods of vulnerability.
Apply reuse-first, AI-assisted practices within SDLC and toolchain routines to strengthen security testing and control validation, ensuring traceability, auditability, and alignment to resiliency and security expectations.
Required Qualifications, Capabilities, and Skills
Design and build secure Python solutions (APIs, microservices, automation tools, security utilities) using secure-by-design patterns, least privilege, and defense-in-depth.
Perform secure code development, review, and debugging for Python and adjacent stacks (e.g., containerized workloads, CI/CD), including fixing security defects and improving engineering guardrails.
Demonstrate expertise in cloud and DevOps technologies, including AWS, Google Cloud, Azure, Docker, Kubernetes, Jenkins, and GitLab.
Be skilled in working with databases such as MongoDB, PostgreSQL, and NoSQL systems.
Maintain a strong background in data science and AI, including deep learning, NLP, GenAI, RAG concepts, prompt engineering, and data visualization.
Apply experience in secure coding, model validation, and data privacy.
Exhibit excellent problem-solving, communication, and teamwork skills.
Preferred Skills
Experience with LLM fine-tuning, prompt engineering, and multi-modal AI integration.
Familiarity with CI/CD pipelines and automation tools.
Knowledge of frontend frameworks such as React and Next.js.
Certifications in AI/ML, Kubernetes, AWS, or cybersecurity.
Exposure to cybersecurity frameworks and compliance standards.
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