Operations Enablement Lead Jobs in Texas (NOW HIRING)

Austin, Texas, United States Corporate Functions

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Description

The People Technology team is looking for an AI Enablement Lead to partner with our business owners and engineering teams on re-engineering processes using new emerging technology.This role sits squarely at the intersection of business strategy, technology, process design, and applied AI. The ideal candidate combines operational judgment with technical fluency — understanding both the realities of People processes and the practical considerations required to deploy AI-enabled workflows responsibly at enterprise scale.This is a high-ownership, high-visibility role that will help influence how the People organization evolves its operational model over time.

Responsibilities

• Conduct structured assessments across People functions to identify workflows where AI-enabled automation can deliver meaningful improvements in user experience, effectiveness, scalability and accuracy


• Evaluate opportunities based on operational leverage, business value, process complexity, risk profile, governance considerations, and measurable impact


• Identify repetitive manual work, operational bottlenecks, fragmented workflows, and high-volume process areas suitable for intelligent automation


• Build and maintain a prioritized backlog and roadmap of AI deployment opportunities tied to clearly defined operational KPIs and business outcomes


• Map structured and unstructured data flows across enterprise platforms including Workday, ServiceNow, People EDW, collaboration platforms, project management tooling, and knowledge repositories


• Define human-in-the-loop review checkpoints, escalation paths, auditability requirements, and governance controls within deployed workflows


• Configure and operationalize AI-enabled workflows using APIs, MCP servers, orchestration tooling, integration layers, and enterprise operational platforms


• Translate operational requirements into scalable production-ready solutions with appropriate safeguards, monitoring, documentation, and support models


• Ensure deployed solutions remain maintainable, supportable, and operationally sustainable over time


• Operate and monitor deployed agents and AI-enabled workflows against defined operational KPIs including cycle time, exception rates, accuracy, reliability, adoption, and workflow quality


• Manage evaluations, regression testing, and workflow validation following significant model updates, schema changes, process modifications, or operational dependency changes


• Maintain operational documentation including workflow maps, data lineage, escalation models, governance considerations, and change logs


• Partner cross-functionally with People team leadership, operations teams, engineering, governance, security, and platform teams to ensure deployed workflows align with enterprise standards and operational controls


• Surface emerging automation opportunities as operational needs and organizational priorities evolve


• Drive iterative improvement of deployed workflows through operational feedback loops, usage patterns, testing, and ongoing refinement


• Support adoption of AI-enabled workflows through rollout planning, stakeholder engagement, operational enablement, documentation, and training support


• Establish and maintain People-specific knowledge repositories including process documentation, operational narratives, runbooks, LOB context, and workflow guidance


• Ensure knowledge assets remain current, governed, and accessible in ways that improve both workflow reliability and team self-service capabilities


• Contribute to operational best practices for deploying AI-enabled systems responsibly within enterprise People environments

Minimum Qualifications

• 8+ years of experience in enterprise technology, AI enablement, automation, integrations, digital transformation, or related technical roles.


• Strong experience translating complex business and operational requirements into scalable technology solutions.


• Demonstrated experience designing, building, or enabling automated workflows across enterprise systems and business processes.


• Hands-on technical fluency with APIs, integrations, scripting, SQL/data querying, workflow orchestration, and enterprise application platforms.


• Experience working with AI-enabled applications, agentic workflows, or intelligent automation solutions in an enterprise environment.


• Strong understanding of software delivery and production lifecycle concepts, including development, testing, deployment, monitoring, support, and continuous improvement.


• Experience partnering across engineering, business, security, governance, UX, and platform teams to deliver enterprise solutions.


• Ability to evaluate technical feasibility, operational complexity, business value, risk, and scalability when prioritizing automation opportunities.


• Strong communication and stakeholder-management skills with the ability to translate between technical teams and business partners.


• Ability to operate effectively in ambiguous environments, independently shape problems, and drive initiatives from discovery through implementation and adoption.

Preferred Qualifications

• Deep technical understanding of modern AI application architecture, including LLM-powered applications, tool calling, retrieval and grounding, context management, structured outputs, and agentic workflow orchestration.


• Experience designing agentic architectures such as tool-using agents, orchestrator/worker patterns, multi-agent workflows, event-driven agents, approval-based workflows, and human-in-the-loop systems.


• Experience building or integrating solutions using APIs, MCP servers, orchestration frameworks, enterprise integration layers, and reusable agent/tool interfaces.


• Understanding of enterprise hosting and deployment patterns for AI-enabled applications, including runtime environments, environment separation, scalability, reliability, configuration management, and production support.


• Strong knowledge of security patterns for AI and enterprise applications, including authentication, authorization, service identities, secrets management, least-privilege access, secure API design, auditability, and sensitive-data handling.


• Experience with AI evaluation and observability practices, including tracing, logging, regression testing, quality evaluation, latency and reliability monitoring, failure analysis, and production telemetry.


• Understanding of state management, retries, fallbacks, exception handling, escalation paths, and long-running workflow design for production agentic systems.


• Experience working with structured and unstructured enterprise data, including data access patterns, schemas, SQL, retrieval pipelines, knowledge repositories, and enterprise data platforms.


• Familiarity with software engineering practices such as source control, CI/CD, automated testing, release management, environment management, and operational support.


• Experience identifying reusable AI capabilities, integration patterns, shared services, and platform components that can scale across multiple business functions.


• Strong understanding of responsible AI, privacy, governance, and control requirements in environments involving sensitive employee or enterprise data.


• Experience within People, HR technology, People Operations, People Support, or adjacent enterprise business functions is a plus.

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