Vizient, Inc

Supply Chain

• Lead assigned assessment workstreams and support assessment activities from initiation through delivery of findings and recommendations.
• Execute enterprise assessment frameworks, including stakeholder interviews, operational observations, data collection, and analysis, ensuring alignment with established standards, methodologies, and tools.
• Evaluate financial, operational, and clinical performance through analytics, benchmarking, and assessment against leading practices.
• Identify performance gaps and support development of actionable recommendations, improvement strategies, and implementation priorities in partnership with client and internal stakeholders.
• Quantify improvement opportunities and estimate potential financial and operational impact through data analysis, benchmarking, and performance evaluation.
• Validate assessment findings and develop insights that support measurable improvement opportunities.
• Support development of business cases, recommendations, and implementation priorities by identifying risks, barriers, and performance variances.
• Support assessment-related interactions with client stakeholders and participate in stakeholder interviews, working sessions, and assessment reviews.
• Partner with sourcing, P2P, analytics, clinical integration, and operations teams to gather inputs, validate findings, and align assessment insights.
• Prepare materials and analyses that support presentation of assessment findings and recommendations to client and internal stakeholders.
• Ensure adherence to enterprise standards, operating procedures, and quality controls.

Supply Chain Assessment Manager

Account Manager

• Lead diverse teams to identify, pursue, and manage accounts or opportunities
• Develop and maintain a strong network of relationships with C-suite and operational team critical decision-makers for assigned accounts
• Provide intelligence of the healthcare market and data-driven insights
• Identify service and solution growth opportunities and manage member evolution across assigned accounts/prospects
• Partner with providers to drive their performance in cost, quality, and market share
• Manage forecast, revenue, service levels, profitability and growth of accounts
• Resolve key service delivery issues

Principal, Enterprise Partnerships

Consultant

• Analyze and prioritize construction and facility maintenance categories and align opportunities with Vizient supplier contracts.
• Lead client engagements from project initiation through completion, ensuring successful execution and delivery of measurable outcomes.
• Manage request for proposal (RFP) processes and supplier evaluations for construction, facility maintenance, and medical equipment categories.
• Coordinate activities among client supply chain teams, facilities leaders, construction stakeholders, and third-party contractors.
• Benchmark vendor pricing against contract pricing to identify savings opportunities and support cost reduction initiatives.
• Review client purchasing, contracting, and operational processes and collaborate with legal, risk management, compliance, and other support teams to facilitate contracting activities.
• Review architectural drawings, specifications, and construction documentation to support supplier alignment and contract utilization tracking.
• Cultivate supplier relationships, negotiate pricing and value-added solutions, and identify opportunities to enhance client value.
• Design and execute project work plans, provide status updates, and track, validate, and report realized savings.
• Partner with non-acute market leadership to support strategic initiatives, pipeline reviews, and facilities and construction performance improvement efforts.

Senior Consultant – Facilities & Construction

AI Engineer

• Lead the execution and delivery of enterprise AI engineering initiatives, including AI-powered applications, LLM-enabled workflows, agentic orchestration solutions, AI-enabled automation capabilities, and platform integrations
• Drive day-to-day engineering delivery activities across AI teams, including sprint execution, backlog management, delivery tracking, issue resolution, dependency management, and operational execution
• Implement and operationalize enterprise AI engineering practices, including AI software development lifecycle (SDLC) processes, deployment standards, runtime observability, release management, and engineering quality practices
• Provide technical oversight across solution design, development, validation, deployment, monitoring, optimization, and production support activities
• Support AIOps and LLMOps operational practices, including runtime monitoring, drift detection, observability, incident management, prompt lifecycle management, evaluation execution, operational telemetry, and production reliability
• Develop reusable AI engineering patterns, implementation playbooks, shared services, templates, internal libraries, and engineering accelerators to improve delivery consistency, scalability, and operational efficiency
• Drive adoption of enterprise engineering standards, scalable delivery practices, and shared implementation patterns across AI delivery teams
• Partner with AI Governance, Quality Engineering, Automation, Architecture, and AI Delivery Lifecycle teams to operationalize governance requirements, validation processes, responsible AI controls, runtime safeguards, and secure delivery practices
• Coordinate AI delivery activities across teams, including operational planning, resource management, contractor and vendor alignment, knowledge transfer, and delivery continuity
• Partner with cross-functional stakeholders to support technical feasibility assessments, delivery readiness activities, implementation planning, and engineering sustainability efforts
• Support vendor evaluations, platform implementation initiatives, build-versus-buy assessments, and engineering modernization efforts
• Lead, mentor, and develop engineering managers, architects, engineers, and contractor teams while fostering a high-performing, collaborative, and continuously learning culture
• Communicate delivery progress, operational risks, technical updates, engineering tradeoffs, and implementation recommendations to technical and business leaders
• Research and evaluate emerging AI engineering, automation, observability, orchestration, and platform technologies to support innovation and continuous improvement

Director, AI Engineering – Delivery

Artificial Intelligence

• Lead enterprise AI operational activities, including runtime monitoring, operational support, incident management, production reliability, and operational continuity for AI-powered applications and intelligent automation solutions.
• Establish, implement, and continuously improve AI operational practices, including AIOps and LLMOps processes, runtime observability, operational telemetry, drift detection, release coordination, support workflows, and operational readiness activities.
• Drive runtime stability and service reliability initiatives through production monitoring, escalation management, root cause analysis, operational playbooks, and service continuity practices.
• Support enforcement of runtime governance standards, operational safeguards, human oversight controls, and secure operationalization practices for enterprise AI solutions.
• Ensure operational excellence across AI environments through proactive monitoring, issue prevention, and continuous service improvement efforts.
• Lead initiatives focused on runtime efficiency, operational scalability, inference utilization, supportability, performance optimization, and sustainable AI operations.
• Promote standardized operational processes, scalable support models, automation opportunities, and continuous improvement initiatives across AI operations functions.
• Drive operational maturity by identifying opportunities to enhance performance, reduce operational risk, and improve support effectiveness.
• Partner closely with AI Engineering & Delivery, AI Governance, AI Quality Engineering, Automation, Architecture, Platform Engineering, Security, Infrastructure, and business stakeholders to ensure operational readiness and runtime reliability.
• Coordinate operational execution activities across AI operations teams, including operational planning, vendor and contractor management, issue prioritization, escalation management, knowledge transfer, and delivery continuity.
• Support operational assessments, production readiness reviews, implementation planning, runtime support strategies, and modernization initiatives for prioritized AI capabilities.
• Collaborate with technical and business leaders to align operational practices with enterprise AI objectives and service expectations.
• Lead, mentor, and develop operations managers, engineers, analysts, and contractor resources while fostering a high-performing, collaborative, and continuously learning culture.
• Provide clear communication regarding operational performance, runtime risks, service reliability concerns, optimization opportunities, engineering tradeoffs, and strategic recommendations.
• Establish accountability for operational outcomes while promoting operational discipline, innovation, and continuous improvement.
• Research and evaluate emerging AI operational technologies, observability platforms, automation capabilities, optimization techniques, and runtime management practices to drive innovation and operational effectiveness.

Director, AI Operations – Optimization

Director

• Lead implementation and operationalization of transformation initiatives across client engagements and internal programs.
• Manage matrixed engagement teams and client stakeholders to deliver project plans, support adoption, manage commitments, and achieve client objectives.
• Translate transformation strategy into scalable workflows, operating models, governance structures, and standardized delivery approaches.
• Support development and continuous improvement of client-facing offerings, implementation playbooks, delivery tiers, and operational standards.
• Drive client onboarding, readiness assessments, stakeholder alignment, training, and adoption planning.
• Facilitate governance routines including KPI reviews, issue escalation, implementation tracking, and operational cadence management.
• Lead cross-functional problem solving related to supply chain transformation, operational reliability, procedural readiness, and process standardization.
• Manage implementation risks, dependencies, action plans, and transformation milestones across multiple concurrent initiatives.
• Prepare executive-level implementation updates, operational reviews, and transformation recommendations.
• Use AI tools to improve engagement delivery, workflow development, stakeholder communications, analysis, and implementation planning while ensuring outputs are reviewed for accuracy, quality, confidentiality, and business relevance.

Transformation Director

• Lead the design, architecture, development, and deployment of intelligent automation solutions using Microsoft Power Platform and UiPath technologies
• Serve as a subject matter expert for automation platforms, providing guidance on governance, scalability, best practices, and solution optimization
• Partner with business stakeholders and cross-functional teams to gather requirements, assess business processes, and identify automation opportunities
• Develop and maintain solutions utilizing Power Apps, Power Automate, Power BI, Dataverse, AI Builder, UiPath Studio, UiPath Orchestrator, and related technologies
• Drive automation and modernization initiatives by transforming manual and repetitive processes into scalable, efficient, and reusable solutions
• Lead technical delivery activities including solution design, development, testing, deployment, production support, and continuous improvement
• Ensure automation solutions adhere to enterprise standards for security, reliability, maintainability, and performance
• Collaborate with technical teams to integrate automation platforms with APIs, databases, cloud services, enterprise applications, and third-party systems
• Troubleshoot and resolve complex technical issues involving workflows, integrations, automation orchestration, and platform performance
• Lead automation projects and workstreams, managing timelines, priorities, deliverables, risks, and stakeholder communications
• Develop reporting, dashboards, and analytics solutions that improve operational visibility and support data-driven decision making
• Communicate technical concepts, recommendations, and project updates effectively to both technical and non-technical audiences
• Mentor automation engineers, developers, and analysts through coaching, technical guidance, peer reviews, and knowledge sharing
• Support the advancement of automation governance frameworks, standards, and Center of Excellence (CoE) practices
• Research and evaluate emerging automation, AI, and low-code technologies to drive innovation and continuous improvement

Lead Analyst, AI Intelligent Automation

DevOps Engineer

• Lead and scale enterprise AI Quality Engineering capabilities supporting AI-powered applications, LLM-enabled workflows, intelligent automation solutions, agentic systems, and enterprise AI platforms.
• Establish and operationalize AI-native quality engineering frameworks, validation methodologies, testing standards, runtime assurance practices, and scalable delivery processes.
• Drive modernization of traditional quality engineering and test automation practices to support AI-enabled workflows, probabilistic systems, intelligent orchestration, and evolving healthcare business processes.
• Lead AI validation strategies, including functional testing, prompt testing, workflow validation, regression testing, release readiness, runtime quality assurance, and production reliability.
• Partner with AI Engineering, Data, Security, Governance, Clinical, and Operational teams to ensure quality, reliability, scalability, and successful deployment of enterprise AI solutions.
• Implement quality controls, governance-aligned testing practices, validation evidence processes, and risk mitigation strategies that support responsible AI adoption and regulatory compliance.
• Advance enterprise observability, telemetry, monitoring, and runtime quality practices to improve traceability, reliability, and confidence across AI-enabled systems.
• Lead AI Quality Engineering delivery activities, including organizational planning, vendor and contractor management, execution governance, tooling strategy, and capability development.
• Build, mentor, and develop high-performing quality engineering teams while fostering a culture of innovation, accountability, continuous improvement, and engineering excellence.
• Research and evaluate emerging AI quality engineering, testing, automation, observability, and runtime assurance technologies to drive continuous improvement and organizational maturity.

Director, AI Quality & Reliability Engineering

Analyst

• Design, develop, test, deploy, and support intelligent automation solutions using Microsoft Power Platform and UiPath technologies
• Partner with business stakeholders and technical teams to gather requirements, analyze business processes, and identify automation opportunities
• Develop and maintain solutions leveraging Power Apps, Power Automate, Power BI, Dataverse, AI Builder, UiPath Studio, UiPath Orchestrator, and related technologies
• Support automation and modernization initiatives by transforming manual and repetitive processes into efficient, scalable, and sustainable solutions
• Participate in all phases of the solution lifecycle including design, development, testing, deployment, support, and continuous improvement
• Ensure automation solutions align with enterprise standards for security, reliability, maintainability, performance, and scalability
• Collaborate with technical teams to integrate automation platforms with APIs, databases, cloud services, enterprise applications, and third-party systems
• Troubleshoot and resolve technical issues related to workflows, integrations, automation orchestration, and platform performance
• Support project delivery activities including timeline management, issue resolution, stakeholder communication, and deliverable execution
• Develop dashboards, reports, and analytics solutions that improve operational visibility and support business decision-making
• Communicate technical concepts, recommendations, and project updates effectively to both technical and non-technical audiences
• Provide knowledge sharing, technical guidance, and collaborative support to automation team members and business partners
• Support automation governance, documentation standards, Center of Excellence (CoE) practices, and operational excellence initiatives
• Research and evaluate emerging automation, artificial intelligence, and low-code technologies to identify opportunities for innovation and continuous improvement

Senior Analyst, Intelligent Automation

• Lead day-to-day AI Quality Engineering activities supporting AI-powered applications, LLM-enabled workflows, intelligent automation solutions, agentic systems, and enterprise AI platforms.
• Implement and mature AI Quality Engineering practices, including AI-native testing approaches, validation processes, runtime quality controls, reusable testing accelerators, and scalable testing frameworks.
• Coordinate AI validation efforts, including functional testing, prompt testing, workflow validation, regression testing, defect management, release readiness, and production quality assurance.
• Partner with AI Engineering, AIOps, LLMOps, Security, Governance, Clinical, Data, and Product teams to ensure scalable and effective quality engineering processes across AI initiatives.
• Support runtime quality and reliability through observability, monitoring, telemetry analysis, incident support, drift detection, distributed tracing, and continuous improvement initiatives.
• Drive adoption of AI-assisted testing, intelligent automation, reusable test assets, and modern quality engineering practices that improve efficiency and quality outcomes.
• Lead delivery coordination activities including sprint execution, testing planning, issue tracking, risk identification, dependency management, and release support.
• Collaborate with clinical, operational, and engineering stakeholders to validate healthcare workflows, payer operations, and AI-enabled business processes while supporting responsible AI deployment.
• Mentor quality engineers, analysts, contractors, and delivery teams while fostering a culture of continuous learning, engineering excellence, and operational accountability.

Manager, AI Quality – Reliability Engineering

• Lead end-to-end strategic sourcing initiatives across Business Process Outsourcing (BPO), Professional Services, and Revenue Cycle categories, including category strategy development, RFI/RFP execution, supplier evaluation, negotiation, and contract implementation.
• Manage a complex category portfolio by identifying cost drivers, analyzing Kaiser Permanente utilization, and developing sourcing strategies aligned with client priorities.
• Provide strategic guidance to multidisciplinary Kaiser Permanente teams to support informed sourcing and contracting decisions.
• Facilitate stakeholder committees to define requirements, evaluate proposals, and recommend contract awards.
• Develop and negotiate business, financial, and legal terms with suppliers in partnership with internal sourcing and legal teams.
• Evaluate spend data, market dynamics, and supplier proposals to identify savings, standardization, quality, and operational improvement opportunities.
• Present sourcing strategies, outcomes, and performance results to executive-level Kaiser Permanente stakeholders.
• Partner with internal Vizient teams to achieve operational and financial goals for assigned category portfolios.
• Anticipate and respond to external factors such as market conditions, supply risk, and regulatory changes impacting sourcing strategies.
• Build and maintain strong, trust-based relationships with Kaiser Permanente stakeholders and key suppliers to support long-term value delivery.

Service Line Director – BPO, Professional Services, Revenue Cycle

Account Executive

• Lead non-acute spend management strategy and execution across assigned client accounts.
• Align Vizient solutions to client priorities to drive measurable value.
• Identify and implement initiatives that deliver client value and achieve growth targets.
• Expand client engagement to support long-term account growth.
• Build and sustain relationships with key stakeholders.
• Advise clients on non-labor spend challenges and maintain ongoing engagement.
• Partner across internal teams to deliver a seamless One Vizient experience.
• Leverage analytics, business intelligence, and market insights to guide decision-making.
• Establish and monitor KPIs and communicate value delivered to clients.

Senior Account Executive, Non-Acute Spend Management

Pharmacist

• Cultivate and expand pharmacy program opportunities by collaborating with consultants, leadership, and subject matter experts.
• Analyze clinical, contracting, financial, operational, and market trends to deliver insights that inform strategic direction.
• Design and facilitate voice of customer engagements to learn stakeholders’ requirements, strategic agendas, and tactical direction.
• Ensure stakeholders understand where and how to access pharmacy program offerings.
• Develop new and maintain current relationships with assigned stakeholders.
• Synthesize inputs from client discussions and comparative data to generate actionable recommendations.
• Maintain existing and generate new projects and contracts that produce strategic and market insights.
• Guide and influence cross-functional teams to ensure project and contract alignment to stakeholder needs.
• Recommend, diagnose, and validate root causes of healthcare strategic, operational, and clinical challenges.

Pharmacy Executive IV – Spend Management Delivery

• Manage strategic channel partner relationships to drive growth, increase contract penetration, and strengthen member engagement
• Develop and execute account plans, deliver data-driven business reviews, coordinate cross-functional resources, and support joint sales initiatives
• Serve as the primary relationship manager for strategic channel partners
• Develop and execute annual account plans
• Partner with sales and field teams to create member-specific growth strategies
• Manage multiple partner initiatives simultaneously
• Analyze purchasing patterns, contract utilization, and compliance trends
• Conduct business reviews, executive presentations, and strategic planning sessions
• Collaborate with internal business units and category teams
• Educate partners on new and existing contracts, programs, services, and value-added offerings
• Maintain accurate pipeline, activity, and opportunity tracking within Salesforce

Senior Account Executive, Channel Partner

Business Intelligence Analyst

• Develop, maintain, and enhance Power BI dashboards and reports focused on sales performance, resource management, and project financial
• Use SQL, Databricks, Power Query, Excel, and other tools to extract, transform, clean, validate, and analyze data from multiple systems
• Build and maintain scalable data models that support accurate, timely, and consistent business reporting
• Automate recurring reporting, manual processes, and operational workflows to improve efficiency and reduce administrative burden
• Partner with consulting business unit leaders to understand reporting needs, define key performance indicators, and deliver insights to support decision-making
• Support the consulting operations team by identifying opportunities to improve processes, data quality, reporting accuracy, and workflow consistency
• Collaborate with finance, sales operations, resource management, project delivery, and technology teams to ensure alignment in reporting requirements and data usage
• Perform ad hoc analysis to answer business questions, identify trends, highlight risks, and uncover opportunities for operational improvement
• Monitor report performance, troubleshoot data issues, and implement enhancements to improve usability, reliability, and scalability
• Create and maintain documentation for reports, data definitions, business logic, workflows, and standard operating procedures
• Promote best practices in data visualization, dashboard design, data governance, and self-service analytics to drive continuous improvement in business intelligence