Artificial Intelligence

• Lead the design, development, deployment, and support of agentic AI solutions for business specific use cases and workflows
• Partner with business stakeholders, product teams, and domain experts to understand requirements and translate them into effective technical solutions
• Oversee day to day engineering execution for forward deployed AI initiatives, including planning, prioritization, delivery, and operational readiness
• Ensure AI solutions are scalable, reliable, maintainable, and aligned with enterprise architecture
• Drive integration of AI solutions with business systems, data sources, and operational processes

Director, AI Forward Deployed Engineer

• Build and maintain features for our agentic applications, writing clean, tested, and well-documented code under the guidance of senior engineers.
• Assist in developing and debugging components of our agentic workflows, learning how stateful agents are structured, deployed, and monitored.
• Write scripts and small utilities that improve developer experience, automate repetitive tasks, and support the team's CI/CD pipelines.
• Contribute to unit and integration tests, help triage bugs, and participate in code reviews to learn and uphold team standards.
• Keep technical documentation current as features evolve, making it easier for the whole team to move quickly.

AI Orchestration Engineer Intern

• Own Workday architecture & configuration
• Own the business process framework inside Workday — how approvals route, how tasks trigger, how workflows sequence across the employee lifecycle
• Configure and maintain security roles so the right people have access to the right data
• Build and maintain custom reports and calculated fields that feed compensation decisions, headcount tracking, and org management
• Design and maintain integrations between Workday and our broader People tech stack — payroll, Pulley, and Ashby — so data flows automatically without manual reconciliation
• Audit and continuously improve system configuration as the org grows and business needs change
• Serve as the internal Workday expert — the person who knows what the system can do and pushes us to actually use it
• Identify manual, repetitive workflows across the People function and build automations that eliminate them
• Evaluate and implement AI tools relevant to People Operations, compensation, and systems administration
• Partner with the Total Rewards & Infrastructure Lead to build and execute a People AI roadmap
• Stay close to what Workday is releasing natively on AI and automation and bring those capabilities in-house
• Build and maintain the data infrastructure that powers compensation decisions — salary bands, job architecture, and leveling frameworks
• Support the annual compensation review cycle from a systems and data perspective
• Maintain equity administration in Pulley and ensure clean data across grant history, vesting schedules, and terminated employee records
• Partner with Total Rewards & Infrastructure Lead on compensation modeling and scenario analysis as we scale

People Systems – AI Analyst

• Lead technical discovery and design agentic AI solutions for enterprise clients
• Write production-grade code and integrate systems with enterprise platforms
• Build and tune retrieval pipelines and implement production observability
• Stay engaged through cutover and the first production iteration cycle

Forward Deployed Engineer, Agentic AI

• Monitor the performance of Agentic Capabilities as they autonomously process various ticket types.
• Ensure seamless integration of AI agents into new or existing workflows, optimizing for efficiency and accuracy.
• Review fallout tickets (cases where AI agents cannot resolve issues) within a workflow management tool.
• Diagnose root causes, make necessary corrections, and re-ingest updated information to the AI system.
• Ensure all fallout tickets are actioned within a 48-hour window; unresolved tickets revert to the human-worked queue.
• Analyze fallout patterns to identify knowledge gaps, process inefficiencies, or opportunities for AI improvement.
• Develop and implement training protocols to enhance Agentic Capabilities, leveraging prompt engineering, model validation, and knowledge base updates.
• Collaborate with cross-functional teams (product, engineering, support) to align AI behaviors with business needs and compliance requirements.
• Maintain and update the agent knowledge base, ensuring accurate, current, and comprehensive content for AI agents.
• Document training methodologies, ticket resolutions, and process improvements for knowledge sharing and auditing.
• Validate AI performance through systematic review, testing, and user/stakeholder feedback.
• Ensure all processes comply with regulatory standards, ethical guidelines, and company policies.
• Track and report on key metrics: ticket resolution rates, fallout frequency, review turnaround times, and AI improvement outcomes.
• Communicate insights, best practices, and recommendations to stakeholders and leadership.

Senior Specialist, Quality/M&P/Process – AI Training Manager

• Lead the design, development, deployment, and support of agentic AI solutions for business specific use cases and workflows.
• Partner with business stakeholders, product teams, and domain experts to understand requirements and translate them into effective technical solutions.
• Oversee day to day engineering execution for forward deployed AI initiatives, including planning, prioritization, delivery, and operational readiness.
• Ensure AI solutions are scalable, reliable, maintainable, and aligned with enterprise architecture, engineering standards, and governance requirements.
• Drive integration of AI solutions with business systems, data sources, and operational processes to enable effective end to end workflows.
• Monitor solution performance, user feedback, and operational outcomes to identify enhancements, resolve issues, and support continuous improvement.
• Collaborate with platform, data, infrastructure, and security teams to leverage shared capabilities and ensure compliant, efficient deployment.
• Communicate progress, technical decisions, risks, and business impact to senior leaders and cross functional stakeholders.

• Own end-to-end governance of enterprise Quality platforms.
• Define and enforce standards, workflows, and operating models across all Quality tools.
• Establish governance for tool lifecycle management.
• Lead strategy, deployment, and value realization of AI-driven Quality solutions.
• Identify and scale high-impact AI/automation use cases.
• Ensure AI solutions are trusted, explainable, and aligned with business and regulatory requirements.
• Own integration of Quality systems with enterprise data and analytics platforms.
• Define data models, reporting standards, and metrics governance.
• Lead alignment across Engineering, Software, Safety, IT, and Global Quality.
• Simplify and standardize Quality processes.

Quality Systems Manager – Digital Quality Platforms, AI

• Lead the design and execution of Baylor Genetics’ enterprise data and AI strategy
• Establish a scalable data platform, enabling advanced analytics, and driving AI adoption across the organization
• Build and lead a high-performing team while partnering across Technology, Genomic Sciences, Operations, and Commercial teams
• Define and implement the enterprise data platform architecture (e.g., Databricks, Snowflake, Azure ecosystem)
• Establish a single source of truth across clinical, operational, and financial data
• Design scalable data ingestion, processing, and storage frameworks
• Ensure interoperability across systems including LIMS, reporting platforms, and enterprise applications
• Define and execute the company-wide AI strategy
• Identify and prioritize high-value AI use cases (clinical, operational, customer-facing)
• Lead development and deployment of AI/ML models and GenAI solutions
• Establish governance for responsible AI (compliance, explainability, PHI protection)
• Establish enterprise data governance framework (ownership, quality, lineage)
• Ensure compliance with HIPAA, CAP, and other regulatory standards
• Define data access, security, and retention policies
• Partner closely with Security and Compliance teams
• Build enterprise analytics capabilities to support decision-making
• Standardize reporting and KPI definitions across the organization
• Enable self-service analytics for business stakeholders
• Build and lead the Data & AI organization (data engineering, data science, analytics)
• Establish clear operating model and team structure
• Mentor and develop technical and functional leaders
• Partner with Product Engineering and Platform teams for execution alignment

VP, Data and AI

• Operate autonomously to design complex evaluation frameworks and provide structured training data. Expected deliverables include:
• Role-Play Scenario Execution: Creating and executing complex, role-play-based evaluation scenarios that simulate realistic customer service interactions across travel, finance, and technical support domains.
• Model Performance Auditing: Evaluating AI model performance across standardized qualitative and quantitative metrics, focusing strictly on task completion accuracy, conversational naturalness, and audio comprehension.
• Technical Metric Evaluation: Assessing the model's basic computer programming literacy, including its understanding of JSON structures, functions, methods, and ability to reason about structured data within a support context.
• Representative Dataset Generation: Contributing to the development of diverse, high-quality audio datasets that accurately reflect real customer expectations for clarity, efficiency, and natural conversational flow.

German Audio Evaluations Specialist – Freelance AI Trainer

• Operate autonomously to design complex evaluation frameworks and provide structured training data.
• Role-Play Scenario Execution: Creating and executing complex, role-play-based evaluation scenarios that simulate realistic customer service interactions across travel, finance, and technical support domains.
• Model Performance Auditing: Evaluating AI model performance across standardized qualitative and quantitative metrics, focusing strictly on task completion accuracy, conversational naturalness, and audio comprehension.
• Technical Metric Evaluation: Assessing the model's basic computer programming literacy, including its understanding of JSON structures, functions, methods, and ability to reason about structured data within a support context.
• Representative Dataset Generation: Contributing to the development of diverse, high-quality audio datasets that accurately reflect real customer expectations for clarity, efficiency, and natural conversational flow.

Portuguese Audio Evaluations Specialist – Freelance AI Trainer

• Run occupancy planning and workplace strategy analysis using continuous data and AI-native tooling.
• Shape the methodology and define the deliverable for a continuous, board-ready space strategy.
• Inform the product and be credible with customers as a peer who has done their job.

Senior Workplace Strategist – AI-Native Occupancy Planning

• Turn AI transformation ambition into adoption that sticks
• Operationalize the business case, outcomes, and partnerships
• Partner closely with technical leads to ensure adoption
• Build change narratives for affected stakeholders
• Own the initiative plan and track progress against goals
• Produce clear, honest status for stakeholders and governance forums

Director, AI Change Adoption

• Architect and design end-to-end AI/ML solutions for the MediaOS platform
• Define and implement scalable ML pipelines, including data ingestion, feature engineering, model training, deployment, and monitoring
• Lead the design of cloud-native, distributed AI systems leveraging modern frameworks and high-performance computing environments
• Partner with product, data engineering, and platform teams to translate business requirements into robust AI-driven solutions
• Establish and enforce MLOps best practices, including CI/CD, model versioning, observability, governance, and lifecycle management
• Evaluate and integrate emerging AI technologies, including Generative AI, LLMs, and NLP applications where applicable
• Drive data strategy alignment, ensuring high-quality, well-governed datasets to support model development and scalability
• Mentor and guide engineers and data scientists, fostering a culture of innovation, collaboration, and technical excellence
• Architect secure AI platforms, including authentication and authorization models (e.g., RBAC, ABAC)

AI/ML Architect, MediaOS Platform

• Architect, configure, and deploy autonomous AI workflows and task-specific agents.
• Use Google Apps Script to build immediate, agile automation pipelines within the Google Workspace ecosystem.
• Write robust backend logic to establish secure data exchanges via RESTful APIs and JSON payloads.
• Translate unstructured internal HR policies into structured, machine-optimized formats.
• Author highly clean, modular, and dry code in JavaScript and Python.
• Collaborate closely with security and HRIS stakeholders for safe sandbox testing.

AI Capability Intern

• Spend time inside business teams to understand how they actually work — their tools, processes, pain points, and highest-priority outputs.
• Build AI-powered workflows, automations, and custom tools that address real bottlenecks and deliver measurable time savings.
• Help team members develop their own AI skills through one-on-one coaching, working sessions, and structured practice — moving them from early experimentation to confident, independent use.
• Recognize when a solution built for one team applies to others, and do the work to make it reusable across the organization.
• Establish a clear framework for tracking AI adoption progress across business units and report findings to IT leadership on a regular cadence.
• Set documentation standards for the team — every tool, workflow, and lesson learned should be captured so it doesn't live only in your head.
• Help develop Kong's internal AI governance standards in partnership with IT, Security, and Engineering.
• Mentor junior team members and interns, giving them hands-on experience and clear feedback.
• Stay current on AI developments and translate what's relevant into practical applications for Kong's business context.

Senior AI Enablement Specialist – FE

• Run daily dispatch execution from our playbook: load assignment, driver communication, check-calls, and exception handling
• Keep loads covered and customers informed, escalating with judgment when something can’t wait
• Use AI tools daily to research, troubleshoot, draft, analyze, and automate your own work
• Improve the playbook as you go — document what works, flag what doesn’t, and ship a better process every week
• Call out problems early and come with proposed solutions, not just escalations
• Partner with engineering and product to turn recurring manual work into automated workflows
• Track the KPIs of your operation — load coverage, on-time performance, driver utilization — and use them to improve

AI Operations Associate

• Run daily dispatch execution from our playbook
• Keep loads covered and customers informed
• Use AI tools daily to research, troubleshoot, draft, analyze, and automate your own work
• Improve the playbook as you go
• Call out problems early and come with proposed solutions
• Partner with engineering and product to turn recurring manual work into automated workflows
• Track the KPIs of your operation

• Complete one flagship output (research piece, long-form essay, or report)
• Write 1–3 op-eds for target outlets
• Participate in one podcast episode
• Engage in CHT's broader content and media ecosystem
• Attend three mandatory cohort meetings and bi-weekly check-ins

Emerging Voices in AI and Society Fellowship

• Own the alignment and interpretability research agenda for security-domain AI
• Set priorities, personally lead the hardest open problems, and develop methods that explain model behavior mechanistically: not just what models do, but why, and what that implies at the edges of their training distribution
• Build and apply techniques for detecting offensive-misuse signal in model internals, including probing for latent representations of vulnerability knowledge, circuit analysis to understand how security-relevant capabilities are encoded, and activation analysis to surface risk that behavioral testing alone would miss
• Work closely with the adversarial evaluation team to close the loop between what they find in testing and what you find in the weights
• Develop alignment methodology for security-domain AI and own the evaluation framework that makes it measurable
• Contribute original research through publications and external engagement
• Recruit, develop, and retain a lean team of research scientists

Director, AI Alignment and Interpretability

• Design, develop, test, and deploy features that directly impact CrowdStrike products
• Collaborate with engineers, data scientists, and product teams to build scalable backend systems and AI-powered capabilities
• Deploy machine learning techniques to develop highly accurate models
• Solve complex technical problems with a high degree of ownership and autonomy
• Build and maintain reliable APIs, data pipelines, and backend services
• Apply machine learning and AI technologies to improve product capabilities and user experiences
• Develop automated tests and contribute to overall software quality and reliability
• Participate actively in architecture, design, and code reviews
• Continuously learn new technologies, industry trends, and emerging research relevant to AI and cybersecurity
• Contribute ideas and innovations in a fast-paced, customer-focused environment

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