Artificial Intelligence

• Champion Agile principles and practices across AI and data-focused teams, driving adoption and continuous improvement
• Coach product owners, engineers, and business stakeholders on Agile frameworks such as Scrum, Kanban, or SAFe
• Facilitate core Agile ceremonies (sprint planning, stand-ups, reviews, retrospectives) to ensure effective team execution
• Foster a culture of transparency, collaboration, and iterative delivery across cross-functional teams
• Partner with technical teams (data science, ML engineering) and business leaders to translate AI use cases into actionable backlogs and sprint goals
• Guide teams in delivering AI/ML solutions iteratively, accounting for experimentation, model training, and validation cycles
• Align delivery plans with business objectives, ensuring AI initiatives provide measurable value
• Support prioritization of work based on business impact, technical dependencies, and data readiness
• Enable collaboration across diverse teams, including data scientists, engineers, product managers, and domain experts
• Remove impediments and escalate risks impacting delivery timelines or outcomes
• Act as a liaison between technical and non-technical stakeholders to ensure shared understanding
• Define and track Agile and AI-specific performance metrics (e.g., velocity, cycle time, model performance indicators)
• Ensure AI delivery adheres to governance, compliance, and ethical standards (e.g., bias, data privacy)
• Facilitate retrospectives and apply learnings to improve delivery effectiveness and team maturity
• Promote data-driven decision-making and experimentation
• Support enterprise Agile transformation efforts, particularly within AI and digital initiatives
• Influence leaders and stakeholders to adopt Agile ways of working and AI-enabled delivery models
• Drive mindset shifts toward iterative development, experimentation, and continuous learning

AI Agilist

• Lead a cross-functional product pod of Solution Consultants, Pega Configurators, and Business Analysts to deliver Pega-based workflow automation solutions aligned to business priorities.
• Provide day-to-day product direction, delivery oversight, mentorship, and issue resolution support to help the team meet commitments and maintain high execution standards.
• Own solution delivery from discovery and design through configuration, testing, deployment, and post-implementation feedback, with a focus on quality, usability, scalability, and control readiness.
• Work hands-on within Pega App Studio and Dev Studio to support solution design, configuration, testing, and implementation of workflow capabilities.
• Partner with architecture and engineering teams to ensure solutions align with platform architecture, technical standards, security requirements, and software delivery lifecycle expectations.
• Translate operational pain points, process inefficiencies, and business needs into clear product requirements, workflow designs, user stories, acceptance criteria, and delivery plans.
• Partner directly with operational leaders and business stakeholders to assess opportunities, shape solution options, manage expectations, and drive alignment on scope, priorities, benefits, and delivery timelines.
• Establish and monitor success measures for delivered solutions, including adoption, operational efficiency, user experience, quality, risk reduction, and other relevant business outcomes.
• Elevate product management practices across the team by improving intake, prioritization, roadmap planning, stakeholder communications, and outcome measurement.
• Identify and help resolve risks, issues, impediments, and dependencies that could impact delivery quality, control effectiveness, or business outcomes.
• Foster a collaborative, inclusive, and accountable team environment that supports talent development, clear communication, continuous improvement, and operational excellence.

Pega Product & Solution Delivery Lead – AI Case Management

• Assist with defining and executing the organization’s AI adoption roadmap, aligning with business objectives.
• Lead development of AI agents, workflows, and prompt engineering to automate and optimize processes.
• Establish governance for responsible AI use, ensuring compliance, security, and ethical standards.
• Evaluate emerging AI technologies (Copilot, Azure AI, AI Foundry) and integrate them into enterprise solutions as agreed.
• Lead in establishing a Centre of Excellence. Promote best practices, reusable components, and knowledge sharing.
• Support teams by leading discovery workshops, requirements gathering, and solution design sessions.
• Create reusable AI components and frameworks to accelerate delivery across teams.
• Design, develop, and implement end-to-end solutions using Power Apps, Power Automate, Power BI, and Dataverse.
• Manage and enhance governance tools like the CoE Toolkit.
• Integrate Power Platform with Microsoft 365, Salesforce, NetSuite, GTM systems, and other business tools.
• Develop a community to support AI adoption across the business to enable knowledge sharing and effective delivery.
• Partner with business units to identify opportunities for AI-driven transformation.
• Support UAT, deployment, training, and post-go-live troubleshooting for AI and Power Platform solutions.
• Document AI architecture, workflows, security roles, and governance models.
• Ensure all solutions meet accessibility, security, and compliance standards.

AI Lead – Power Platform

• Lead the strategy, engineering, and applied AI capabilities that power search, discovery, and product finding platforms across digital channels.
• Drive measurable business outcomes through relevance optimization, search platform modernization, machine learning, GenAI, and agentic commerce capabilities.
• Implement the technology strategy and execution for GPC’s unified commerce platforms.
• Exhibit a deep understanding of modern technology stack and agile delivery models.
• Partner with Product and cross-functional GPC teams to define and execute a vision for AI-powered search that improves conversion, revenue, and customer productivity.
• Implement the technology platforms architecture and execute on roadmap to support build out the new commerce related capabilities needed for the unified commerce strategy.
• Lead the engineering teams responsible for search platform architecture, scalability, reliability, and performance.
• Drive modernization of search infrastructure leveraging cloud-native and AI-enabled technologies.
• Build and scale Search Science capabilities including relevance tuning, ranking models, semantic search, vector search, recommendations, and personalization.
• Responsible for delivery and support of the platform.

Senior Manager, Search Platforms – AI

• Drive end-to-end delivery of production AI platforms
• Lead solution architecture, orchestrate model pipelines, and design multi-agent workflows
• Create reusable SDKs and frameworks
• Collaborate across product, engineering, security, and governance teams
• Ensure AI systems are scalable, observable, cost-efficient, and compliant
• Define design patterns and optimize operational pipelines
• Enable internal reuse of proven solutions
• Own the full lifecycle from architecting secure, compliant solutions to deploying and scaling them in production
• Work with Azure OpenAI, Azure AI Search, multi-agent orchestration, and API integrations for EHR, CRM, and member portals

Senior Artificial Intelligence Engineer

• Lead a team responsible for identifying, designing, and executing AI and automation solutions
• Lead a team of approximately 10 automation professionals
• Ensure high-quality delivery and effective support for internal stakeholders
• Oversee identification and definition of AI and automation solutions aligned to business strategy
• Review and guide design recommendations
• Provide hands-on design direction for complex initiatives
• Partner with delivery, engineering, and architecture teams
• Serve as a senior liaison between business leaders and technical teams
• Guide evaluation of emerging AI and automation technologies

Operations Manager – AI & Automation Design

• Own the enterprise AI feasibility function , providing authoritative guidance on Model selection (traditional ML, GenAI, agentic AI)
• Approved platforms, tools, and services
• Architectural patterns and trade‑offs
• Act as the primary technical advisor to business and technology teams evaluating AI use cases.
• Ensure teams are guided toward enterprise-approved solutions that accelerate delivery and reduce long‑term operational risk.
• Identify delivery blockers early (data readiness, platform onboarding, governance dependencies) and drive resolution.
• Establish and maintain AI playbooks, standards, and best‑practice frameworks for internal teams.
• Sponsor and guide enterprise‑wide workshops, training, and knowledge‑sharing initiatives.
• Provide consultative guidance on AI solutions and architecture, partnering with product, engineering, and business teams to shape use cases, design patterns, and implementation approaches.
• Act as a trusted advisor to teams evaluating AI feasibility, trade‑offs, and architectural alignment with enterprise standards.
• Build and lead an AI Center of Excellence to drive talent strategy, mentorship, and continuous capability development.
• Provide leadership and oversight for enterprise MLOps practices, including CI/CD, model registry, and automated rollback.
• Ensure AI systems meet regulatory, security, and privacy standards in collaboration with risk and compliance stakeholders.
• Define and review SLAs, KPIs, and observability standards for AI services, ensuring operational excellence and accountability.
• Set the architectural vision for a scalable, modular AI ecosystem spanning data ingestion, feature stores, training infrastructure, and inference.
• Champion standards for model governance, including versioning, data lineage, explainability, and auditability.
• Evaluate emerging AI technologies and approaches, and define adoption roadmaps aligned with business value and risk tolerance.
• Own the strategic evolution of the on‑prem AI platform stack (e.g., Airflow, Elasticsearch) and its operating model.
• Ensure delivery of self‑service platforms, APIs, and tooling that enable teams to innovate efficiently and safely.
• Partner with cloud, DevOps, and security leaders to balance performance, cost efficiency, scalability, and compliance.

AI/ML Deployment and Enablement Lead

• The Managing Director owns market outcomes across revenue, margin, client satisfaction, team engagement, and practice depth.
• Own and grow the Minneapolis Data & AI pipeline — from initial relationship to signed engagement.
• Lead executive-level client conversations across data strategy, AI enablement, and platform modernization.
• Develop and execute the Data & AI go-to-market strategy for Minneapolis, aligned to firmwide direction in collaboration with Pioneer’s National Solutions Team.
• Drive account planning and expansion within existing clients across sectors, with an eye toward industries where data and AI create high strategic value.
• Represent Pioneer at industry events, conferences, and thought-leadership forums to build market visibility.
• Serve as executive sponsor on key client engagements, ensuring quality, risk management, and satisfaction.
• Translate client business problems into concrete data and AI solutions leveraging Pioneer’s capabilities.
• Oversee utilization strategy and resource deployment across the practice portfolio.
• Lead the integration of Pioneer’s data engineering/analytics and AI/ML teams into a unified, high-performing practice.
• Build and retain a strong team of data engineers, analytics consultants, data scientists, and ML engineers.
• Drive talent acquisition, onboarding, and career development in partnership with Pioneer’s talent processes.
• Own annual business planning for the Minneapolis Data & AI practice, including revenue targets, headcount, and investment priorities.

Managing Director, Data & AI

• Define and own the AI product strategy, outcomes, and end‑state vision, aligning WIM AI initiatives to enterprise priorities and measurable business value.
• Lead end‑to‑end product management for complex, enterprise‑grade AI platforms, solutions, and capabilities, ensuring scalability, governance, and operational readiness.
• Partner closely with the WIM Head of AI & Digital Asset Platforms to shape AI roadmaps, investment decisions, prioritization, and product tradeoffs.
• Translate business problems into prioritized AI use cases, value cases, and delivery plans across advisor, client, and operations domains.
• Drive cross‑product AI portfolio management, identifying dependencies, synergies, and risks across platforms, workflows, and distribution channels.
• Guide long‑term AI solution delivery, accounting for regulatory requirements, responsible AI principles, data dependencies, and enterprise technology constraints.
• Articulate AI product vision and roadmap; define scope; prioritize backlogs; and support platform evolution, model deployment, and workflow integration.
• Own key business, adoption, operational, and risk metrics, embedding governance, controls, and compliance requirements throughout the AI product lifecycle.
• Engage and align cross‑functional teams and external partners, including Product Owners, Engineering, Data, Risk, Compliance, Legal, Operations, and vendors.
• Serve as a trusted advisor to senior leadership, translating complex AI, regulatory, and market considerations into clear product direction and execution plans.

Executive Director – Artificial Intelligence, AI

• Provide pre- and post-sales technical and benchmarking support to enable HPC or AI customer opportunities
• Collaborate with HPE product engineering, product management, and marketing to influence current and future product capabilities and direction
• Evaluate emerging technologies and assess their impact on product differentiation (performance and features) for key customer applications
• Develop and maintain current knowledge of HPE and competitor HPC/AI products and performance optimization techniques to ensure the team continues to deliver high-quality benchmark results
• Lead application-focused performance studies and projects, and author technical reports and papers that communicate findings and recommendations

Senior Performance Engineer, HPC & AI

• The AI Strategy & Transformation is a senior enterprise leader responsible for shaping how AI strategy is translated into scalable, high-impact outcomes across the organization.
• Partner with the Head of AI Strategy to operationalize enterprise AI strategy through roadmaps, RAI principles, and transformation priorities.
• Drive cross-business alignment to ensure AI initiatives reinforce a unified enterprise direction while enabling domain-specific tailoring.
• Enable AI product/platform strategy execution by translating strategy into reusable enterprise capabilities, reference patterns, and adoption plans.
• Partner with Risk, Compliance, Legal, Privacy, Security, and Model Risk Management to align AI initiatives with enterprise governance requirements and emerging regulatory expectations.
• Establish and scale governance mechanisms that support safe and compliant AI deployments.
• Shape and prioritize high-impact AI use cases and transformation initiatives; ensure the pipeline balances quick wins, strategic bets, and foundational platform capabilities.
• Implement measurement frameworks to evaluate business impact, efficiency, risk reduction, customer outcomes, and ROI for AI deployments; continuously inform strategy and solution improvements based on measurable outcomes.
• Drive organizational engagement through outreach, workshops, and collaborative forums to instill an AI-first mindset and best practices at scale.
• Guide large, cross-functional AI programs to ensure alignment, execution discipline, and value realization across business and technology teams.
• Identify and support breakthrough transformation initiatives to accelerate readiness and adoption across the organization.
• Influence without direct authority to align stakeholders across business lines, enterprise architecture, engineering, data, operations, and risk functions.
• Lead strategic AI vendor and ecosystem partnerships across hyperscalers, AI platforms, data providers, and system integrators.

AI Strategy – Transformation Leader

• Architect internal productivity revolution and analyze workflows.
• Rapidly prototype and refine agentic solutions.
• Help build and deploy production grade AI agents.
• Integrate AI agents with enterprise resources.
• Define and track productivity & ROI.
• Stay at the forefront of AI developments in the media industry.

Director, Applied AI – Strategy

• Lead development of scalable applications in Node.js, Express/NestJS, React, and Cosmos DB.
• Drive spec-driven Agile delivery with AI-assisted workflows.
• Deploy AI chatbots via Copilot Studio and custom LLM frameworks.
• Architect auth flows (Auth0, Okta) for secure access to AI-driven features.
• Implement self-healing E2E test suites in Playwright with AI-powered auto-updating of test scripts.
• Build observability workflows for automated alerting and anomaly detection.
• Champion code quality, security and governace, and CI/CD excellence across all repos.
• Monitor and optimize cloud spend and implement tagging, rate-limiting, and auto-scaling.
• Coach junior and mid-level developers and manage a team of full-stack engineers.

Senior Technical Development Lead – AI-Native Transformation

• Serve as a client-facing leader on AI engagements - advising executive stakeholders on AI strategy, capability roadmaps, build vs. buy decisions, platform selection, and adoption, while translating ambitious business goals into pragmatic, sequenced AI investment plans.
• Lead the end-to-end design, development, and deployment of AI and ML solutions for clients - including classical machine learning models, agentic AI systems, chatbots, custom copilots, and RAG-based applications - primarily on Azure, with working fluency in AWS or GCP as needed.
• Architect and build solutions hands-on across modern data platforms (Databricks, Microsoft Fabric, Snowflake) and AI services; own design across data pipelines, model development and deployment, prompt and agent design, vector retrieval, integration, security, and responsible AI - ensuring solutions are intuitive, scalable, and production-ready.
• Integrate AI applications with enterprise data sources, CRM systems, operational platforms, and APIs (REST, GraphQL) ensuring solutions are robust, secure, governed, and sustainable at scale.
• Rapidly deliver POCs and MVPs to validate ideas and assumptions using agile development approaches, and build reusable accelerators and reference architectures that scale across engagements.
• Coach clients and Pioneer team members on AI capabilities, drive adoption of the tools you build, and mentor consultants — collaborating with strategists, developers, and change practitioners to deliver cohesive, responsibly-designed AI systems.
• Lead client engagements end to end - managing project teams, owning delivery and quality, navigating executive stakeholders, and bringing the consulting rigor and structured problem-solving that Pioneer is known for.
• Help grow Pioneer’s AI practice by contributing to thought leadership, points of view, account growth, and the development of repeatable offerings; stay ahead of evolving AI technologies, Copilot extensions, LLM advancements, and responsible AI best practices.

Principal Consultant, Artificial Intelligence Engineer

• Set and execute a bold vision for integrating AI, data science, and automation across all Commercial Banking client and colleague experiences
• Lead cross-functional workstreams across product, technology, marketing, and operations to deliver measurable business outcomes
• Serve as a strategic advisor, identifying emerging technologies and trends that can be leveraged to drive value
• Champion a culture of innovation, agility, and data-driven decision-making across the organization
• Act as a change agent, driving adoption of digital and AI capabilities embedded within business processes and workflows
• Develop and lead the Commercial Bank’s Digital & AI strategy, ensuring alignment with enterprise objectives and client needs
• Identify high-value use cases that drive efficiencies and enhance experiences using automation, AI, and Generative AI across customer and colleague journeys
• Foster strong collaboration with Commercial business leaders and the AI Center of Excellence (COE) to ensure alignment on priorities and outcomes
• Drive execution and delivery of the AI roadmap in partnership with the AI COE and technology partners
• Measure, track, and communicate the business impact of AI initiatives to stakeholders and senior leadership

Executive Director – Digital & AI Transformation

• Own and govern end-to-end integration architecture across telephony platforms, APIs, and enterprise data systems
• Design and implement real-time and batch data pipelines supporting AI and analytics workloads
• Architect secure API integrations using enterprise patterns such as API gateways, OAuth 2.0, and event-driven designs
• Enable secure data exposure and transaction execution for AI platforms
• Establish reusable integration patterns for vendor evaluation and production scalability
• Serve as the primary technical liaison between internal teams and external AI/telephony vendors
• Ensure observability, traceability, and auditability of integrations using modern tooling (e.g., OpenTelemetry)
• Collaborate daily with architecture leadership, IVR teams, data, security, network, and infrastructure partners

Data & Integration Architect – Voice AI, IVR

• Lead the evaluation and production readiness of AI products and capabilities across the enterprise.
• Ensure solutions are scalable, secure, governable, and aligned with enterprise architecture standards.
• Partner closely with Legal and Information Protection to meet regulatory and risk management requirements.
• Conduct GenAI intake reviews, applying enterprise AI guardrails and standards.
• Partner with solution teams and area technology leaders to clarify requirements and reduce redundancy.
• Steward enterprise AI architecture principles and requirements during path-to-production reviews.
• Advise cross-functional teams on solution architecture and data protection optimization.
• Serve as a strategic advisor on enterprise AI capabilities and opportunities.

Senior Architecture Advisor – AI Enablement

• Drive the development and deployment of AI-enabled tools in CRE functions
• Design, test, and optimize AI prompt frameworks
• Analyze loan-level and market data for actionable insights
• Build dashboards for credit committees and portfolio reviews
• Streamline underwriting workflows via automation and AI
• Support the development of structured CRE data environments
• Ensure adherence to data governance and model risk management standards

CRE AI Analyst

• Own an enterprise portfolio of agentic AI use cases; shape multi-quarter roadmaps tied to business strategy, scalability and measurable outcomes; define success metrics (value, quality, portability) and manage trade-offs across initiatives.
• Define agentic framework to conduct end-to-end discovery (diagnostics, data/system constraints, user journeys) to identify high-value agentic opportunities; translate pain points into agentic AI solutions (tools/actions, guardrails, autonomous or human-in-the-loop) and delivery plans.
• Build and defend business cases (cost, revenue, CX improvement); secure executive alignment; establish benefits measurement (baseline, attribution, measurement) and manage realization through adoption and continuous improvement.
• Coordinate with cross-functional squads (product, AI engineering, data science, architecture, operations) and external partners to deliver pilots and scaled deployments; manage scope, dependencies, risks, and delivery quality; run executive steering and agentic AI program governance.
• Partner with Responsible AI leader to implement controls for data handling, model/vendor risk, explainability, and operational resilience; ensure appropriate guardrails (policy, content filtering, escalation paths) for production agent use.
• Lead launch planning, training, communications, and hypercare; drive stakeholder readiness and measurable adoption; establish feedback loops and a backlog for post-launch enhancements across business units.

AI Delivery Leader

• Define Enablement’s AI application strategy, including standards, frameworks, and reusable patterns that support consistent AI adoption across the field.
• Deconstruct Sales Engineer workflows and identify opportunities where AI can automate, augment, or accelerate technical sales activities.
• Apply deep technical expertise comparable to a Cohesity Sales Engineer to ensure AI solutions align with real customer engagement requirements.
• Partner with Sales Engineering leadership, Enablement stakeholders, and AI partners to design, pilot, and scale AI‑enabled tools.
• Collaborate across Enablement functions, including AE Enablement and Renewals Enablement, to identify and prioritize AI use cases that can be reused at scale.
• Work closely with the CIO AI and IT teams that own the core AI platform, providing application‑level requirements, guidance, and enablement perspective.
• Define instrumentation, dashboards, and success metrics to measure adoption, effectiveness, and business impact of AI‑enabled workflows.
• Serve as a trusted advisor to Field sellers, Enablement leaders, Finance, and Revenue Operations, translating complex AI concepts into clear, actionable guidance.

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