https://kybernan.ai/assets/about_.jobs-BT_Azlkg.js

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Deliver secure-by-design foundational capabilities that enable AI adoption.",sections:[{heading:"Responsibilities",bullets:["Enable secure AI adoption by ensuring secure-by-design principles and guardrails are incorporated in AI digital capabilities across the enterprise.","Define cybersecurity requirements, guardrails and architectures for AI security solutions (AI Security Posture Management, Unsanctioned AI monitoring, API gateways, MCP Servers).","Establish AI cybersecurity governance for IT technologies across all technology functions.","Lead security research proposals and proofs of concept for AI technologies.","Consult as a subject matter expert on cybersecurity risk assessments for AI technologies."]},{heading:"Selection Criteria",bullets:["Functional Expertise: Experienced in AI cybersecurity with a risk-based approach to designing, testing, and applying AI security solutions. Familiar with ISO 42001, NIST AI RMF, OWASP Top 10 for LLM and Agentic Applications, MITRE ATLAS, and NIST 800-53 controls.","Domain Knowledge: Skilled in designing and implementing protection and monitoring for AI cybersecurity technologies.","Technical experience in one or more cybersecurity domains: Application Security, Data Security, Identity and Access Management.","Proficiency in AI vulnerability assessment and exploitation, and foundational architecture components needed to secure AI adoption.","Sets clear expectations, communicates technical concepts transparently, solves complex problems independently and in teams, and challenges n

1orms.","Mentors others in AI cybersecurity and promotes a 'secure by design' culture."]},{heading:"Required Qualifications",bullets:["Minimum 5 years related work experience in cybersecurity with increasing levels of responsibility.","Technical experience in one or more cybersecurity domains (App Sec, Data Sec, IAM).","General understanding of the cyber threat landscape, including cyber-criminal and cyber-espionage threats.","Previous experience administering cybersecurity technologies and/or supporting cybersecurity operations."]},{heading:"Preferred Education & Certifications",bullets:["Bachelor’s or master’s degree in Cybersecurity, IT, Information Systems, or Computer Science.","Certifications such as GISP, GREM, ISSEP, OSCP or similar.","SAFe Scaled Agile or related scrum/agile project management certification is desirable."]},{heading:"Preferred Qualifications",bullets:["Knowledge of NIST 800-53, MITRE ATT&CK, and the Cyber Kill Chain.","Experience leading cybersecurity assessments (risk, vulnerability) and creating mitigation plans.","Ability to influence and motivate teams across disciplines, cultures, and environments.","Strong written and verbal communication at all levels."]}]},{title:"AI Security Engineer (Senior II)",type:"Contract · $60/hr C2C · Virtual Interview",location:"Remote · USC / GC preferred",summary:"Senior AI Security Engineer II focused on building AI-driven automation within security — starting with IAM and expanding across the broader security organization. A hands-on builder and strategic partner who designs, implements, and scales AI/automation solutions in a security environment. Client: Principal Financial Group. LinkedIn + DL copy required.",sections:[{heading:"AI + Security Integration",bullets:["Build AI-enabled security solutions, including agentic AI.","Apply AI to anomaly detection, UEBA (User & Entity Behavior Analytics), and automated remediation."]},{heading:"Security Automation",bullets:["Develop automation across cloud + enterprise systems, CI/CD pipelines, and Infrastructure as Code (IaC).","Implement policy-as-code, automated controls, and continuous compliance."]},{heading:"IAM (Initial Focus)",bullets:["First major use case is Identity & Access Management.","Then expand into broader security teams."]},{heading:"Must-Have Qualifications",bullets:["8+ years in Security, Engineering, or Technology.","End-to-end experience building AI-enabled systems and automation solutions.","Exposure to agentic / advanced AI systems and security AI use cases (UEBA, anomaly detection).","Comfortable with ambiguity; able to define direction (not just execute).","Strong cross-team collaboration and influencing without authority."]},{heading:"Nice-to-Have / Standout Skills",bullets:["AI Governance / Responsible AI: guardrails, human-in-the-loop design.","IAM background (big plus — starting focus area).","Security frameworks & compliance: NIST, ISO, SOX, PCI translated into automated controls.","Experience in regulated environments (finance, healthcare).","Technical leadership: architecture input, code reviews, senior technical advisor."]},{heading:"Key Responsibilities",bullets:["Identify opportunities: partner with leadership to find areas to automate or improve with AI.","Build solutions: design and implement AI-driven workflows and security automation tools.","Improve security operations: increase efficiency, auditability, and response speed.","Drive standards & strategy: influence architecture, AI adoption, and security best practices."]}]},{title:"Senior Data Governance Manager / Analyst",type:"Onsite 4 days, 1 day remote · Urgent",location:"Irving, TX / Overland Park, KS / Ashburn, VA / Suwanee, GA",summary:"Lead the execution of enterprise data governance frameworks across multiple business domains, embedding governance into delivery workflows and aligning practices to regulatory and risk frameworks.",sections:[{heading:"Responsibilities",bullets:["Lead enterprise data governance frameworks: ownership, stewardship, policies, and standards across business domains.","Define and govern critical data elements (CDEs), business glossaries, and data domains with business stakeholders.","Oversee metadata management, data catalog adoption, and end-to-e

1nd data lineage across operational and analytical environments.","Establish and monitor data quality rules, controls, KPIs, and issue management processes including root cause analysis.","Align governance practices with regulatory and risk frameworks (SOX, GDPR, HIPAA), supporting audits and compliance.","Partner with business, IT, data engineering, analytics, and security teams to drive governance initiatives.","Embed governance into delivery workflows (Agile, SDLC, data pipelines) for scalability and adoption.","Facilitate data issue resolution and decision-making through governance forums and stakeholder alignment.","Communicate governance strategy, metrics, and progress to senior leadership; drive organizational adoption and change."]},{heading:"Qualifications",bullets:["Strong expertise in data quality, metadata management, and data lineage.","Experience with modern data platforms (cloud data warehouses, data lakes, ETL/ELT, BI tools).","Knowledge of regulatory and compliance frameworks impacting data governance.","Demonstrated ability to influence cross-functional stakeholders without direct authority.","Strong communication skills with experience presenting to executive audiences."]}]},{title:"IBM Watsonx Governance Engineer",type:"12+ Months Contract",location:"Remote · USA",summary:"Join our AI CoE practice to design and implement AI governance frameworks, model risk management systems, and responsible AI monitoring solutions using IBM watsonx.governance. Help enterprise clients operationalize trustworthy AI — explainable, fair, compliant, and auditable across the full AI lifecycle. Client: Experis.",sections:[{heading:"Key Responsibilities",bullets:["Implement and configure IBM watsonx.governance for model monitoring, bias detection, explainability, and drift detection.","Design AI governance frameworks aligned to enterprise risk and regulatory requirements (EU AI Act, NIST AI RMF, SOC 2).","Integrate watsonx.governance with third-party model registries, MLOps pipelines, and enterprise data platforms.","Build automated model evaluation pipelines covering fairness metrics, quality thresholds, and compliance checkpoints.","Partner with data science and MLOps teams to embed governance checkpoints into the model development lifecycle.","Support pre-sales engagements: demos, POCs, and technical workshops focused on responsible AI.","Develop dashboards and reporting workflows for AI risk visibility across business and compliance stakeholders.","Contribute to AI governance policy documentation, playbooks, and client-facing accelerators.","Advise clients on model lineage, audit trails, and AI inventory management best practices."]},{heading:"Required Qualifications",bullets:["3+ years of experience in data engineering, MLOps, AI/ML platform engineering, or data governance.","Hands-on experience with IBM watsonx.governance, IBM OpenScale, or equivalent tools (Fiddler, Arthur AI, Aporia).","Working knowledge of model fairness concepts: disparate impact, equalized odds, demographic parity.","Experience with Python, SQL, and ML frameworks (scikit-learn, TensorFlow, PyTorch, or similar).","Familiarity with AI/ML lifecycle tools: MLflow, Kubeflow, SageMaker, Azure ML, or Vertex AI.","Strong understanding of enterprise data platforms and cloud environments (IBM Cloud, AWS, Azure, GCP).","Excellent written and verbal communication for cross-functional stakeholder engagement."]},{heading:"Preferred Qualifications",bullets:["IBM watsonx certifications (watsonx.governance, watsonx.ai, or IBM AI Ethics / Responsible AI credentials).","Knowledge of EU AI Act, GDPR, CCPA, NIST AI RMF, or FINRA/OCC model risk guidance.","Experience with IBM OpenPages for GRC integration with AI workflows.","Background in enterprise data governance platforms (Collibra, Alation, IBM Knowledge Catalog).","Exposure to LLM evaluation frameworks: RAGAS, TruLens, DeepEval, or similar.","Prior consulting, pre-sales, or solutions architecture experience with enterprise AI clients.","Understanding of federated learning, differential privacy, or confidential computing concepts."]}]}

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