Artificial Intelligence

• Partner with leaders across departments to identify, prioritize, and implement high-impact AI use cases that improve business outcomes.
• Build, test, and deploy AI-powered workflows, automations, agents, and productivity solutions using modern AI tools and platforms.
• Evaluate existing processes and redesign workflows to improve efficiency, scalability, and employee experience.
• Establish and maintain AI best practices, governance guidelines, and adoption frameworks that support responsible and effective use of AI across the organization.
• Create and deliver training programs, workshops, documentation, and enablement resources to increase AI literacy and adoption.
• Coach teams to build and maintain their own AI-enabled workflows, creating sustainable capabilities across the business.
• Measure and communicate the impact of AI initiatives through productivity gains, cycle-time reductions, cost savings, and other business metrics.
• Partner with employees and leaders to drive change management efforts, build trust, and encourage thoughtful experimentation with AI.
• Identify opportunities to scale successful use cases across multiple functions and share best practices throughout the organization.
• Serve as BillingPlatform's internal "Customer Zero," helping ensure the company leverages AI internally in ways that align with and strengthen its product vision.
• Collaborate with Product, Engineering, and business leaders to share insights and feedback that inform future AI capabilities and investments.
• Stay current on emerging AI technologies, trends, and tools, and recommend practical applications that create measurable value for the business.

Senior Manager, AI Transformation and Enablement

• Own the full AI engagement arc from discovery through sustained workflow adoption
• Drive requirements and delivery precision to track against plans and surface risks early
• Champion continuous quality through testing and feedback loops during AI engagements
• Hold the R&D feedback loop accountable to ensure field learnings flow back
• Build playbooks to identify reusable patterns and scalable frameworks for the team
• Own engagement economics and track cost structure across active engagements
• This is a field-first role with expected travel to partner locations

AI Engagement Manager

• Design and deliver end-to-end analytics solutions across key HR domains including hiring, performance management, and engagement
• Translate ambiguous business questions into structured data problems and actionable insights
• Build and maintain scalable datasets, dashboards, and metrics frameworks to support leadership decision-making
• Partner with HR, Finance, and business leaders to drive data-informed workforce strategies
• Lead the development of AI-enabled solutions such as copilots, chatbots, and agent-based workflows to scale HR support and impact
• Partner with Technology and data teams to ensure AI solutions are secure, scalable, and integrated with existing systems
• Explore and evaluate emerging AI technologies and tools to improve operational efficiency and enhance employee and HR experiences
• Write and optimize SQL queries to extract, transform, and analyze data from systems such as Snowflake, Workday, and related platforms
• Build and maintain data pipelines and data models to ensure reliable, high-quality datasets
• Integrate data across Workday, recruiting, engagement, and related platforms to create a trusted source of workforce data
• Act as a strategic advisor to HR and business leaders by providing insights and recommendations backed by data
• Communicate findings and recommendations effectively to both technical and non-technical audiences, including executive leadership
• Proactively identify opportunities to improve processes, reduce manual work, and increase self-service capabilities

Manager, People Analytics – AI

• Design, build, and refine AI-powered workflows that support research synthesis, deliverable drafting, proposal coordination, market analysis, and knowledge management.
• Develop and maintain a library of prompt templates calibrated to GEN Advisory’s specific work.
• Manage the practice’s AI knowledge base: organize past project materials, methodologies, and reference content so they are accessible to AI platforms as context for future work.
• Identify bottlenecks in current workflows where AI assistance would have the highest impact; prototype solutions and bring them to the team for feedback.
• Apply AI tools to operations functions: utilization tracking, assignment pipeline reporting, revenue data synthesis, and team reporting, working in coordination with the Director of Operations.
• Conduct market research, demographic analysis, and comparable transaction research to support active client engagements.
• Assist with financial modeling, development pro formas, lease comparisons, portfolio cost analyses, all under direction of senior advisors.

AI Analyst – Government, Education, Non-Profit Advisory

• Serve as a main technical voice for your account team
• Build deep, trusted relationships with C-suite and technical stakeholders
• Demonstrate how Salesforce's capabilities complement OpenAI's models
• Take ambiguous business problems and apply AI-first mindset
• Guide customers through solution evaluation and analysis
• Conduct deep-dive discovery with engineering, IT, and business teams
• Design and deliver compelling product demonstrations
• Orchestrate cross-functional solution teams
• Maintain understanding of the current AI competitive landscape
• Act as a feedback loop between OpenAI and Salesforce’s Product organization

Lead Account SE, Strategic AI

• Set the multi-year strategy for ML, data, and BI
• Build and scale the Data Science / AI, Data Engineering, and BI Engineering organization
• Manage managers and tech leads
• Run performance management, career development, and retention
• Operate as a peer to VP-level leaders across various functions
• Own the architecture, deployment, and operation of the production ML

VP of AI, ML and Data Strategy

• Own Stream’s organic growth engine across search engines, AI assistants, and our website.
• Set the strategy for SEO, AI search (AEO), conversion (CRO), and the marketing data infrastructure used to measure them.
• Execute technical SEO for our marketing website and developer docs - site architecture, crawlability, indexation, schema, structured data, page performance, and resolving technical issues.
• Run on-page optimization across the marketing site and docs: content structure, metadata, internal linking, and keyword targeting.
• Build and execute an off-page and authority program - link acquisition, digital PR, and partnerships - to strengthen domain authority.
• Conduct keyword, competitor, and opportunity research to find and prioritize the highest-value organic plays.
• Partner with content and DevRel to turn editorial and technical content into rankings and qualified organic traffic.
• Monitor organic performance in Google Search Console, Semrush, and analytics tools, and report on qualified traffic, rankings, and signups.
• Build and maintain tracking for how and where Stream shows up across AI assistants and AI-search surfaces.
• Define the methodology and metrics for measuring AI-search visibility, citation, and recommendation.
• Optimize content and site structure to make Stream more likely to be cited and recommended by LLMs and AI-search products.
• Evaluate, select, and implement LLM-visibility tooling - and build custom tracking where off-the-shelf tools fall short.
• Watch emerging AI-search behavior and adjust strategy as the discovery landscape shifts.
• Design, run, and analyze A/B and multivariate experiments on live traffic to improve conversion.
• Find and fix friction in conversion funnels, including signup and SDK-install flows.
• Increase the rate at which organic visitors become signups and active users.
• Help maintain Google Tag Manager (GTM) and GA4, configure event tracking and attribution, and keep marketing measurement accurate and trustworthy.
• Set the organic growth roadmap and priorities — you decide what matters, without waiting for a predefined backlog.

Senior Manager, Organic Growth, AI Search

• Set the Digital & AI direction for the Service Line
• Create an Asset Management specific digital & AI strategy in the context of our 3yr-out vision and strategy of the Asset Management, and the strategic priorities of Industries & Sectors.
• Define and regularly update “digital must-win” areas by conducting competitor analyses and gap analysis within existing portfolio of tools and digital products and partnerships.
• Identify which Asset Management delivery domains and workflows must be redesigned.
• Setup collaboration rhythm with Digital Intelligence, Investment governance, pipeline management approach and prioritization framework, change network, CoPs, etc.
• Set clear objectives for the transformation that link to overall Asset Management performance metrics.
• Collect and pro-actively source digital opportunities and use cases within the organization, in close collaboration with peers in other Service Lines and Industries.
• Kick-start and actively participate in AI studios around the most promising opportunities, to quickly validate and potentially prototype, ideally in real client settings.
• Work closely together with Digital Intelligence counterparts to make buy/build/partner decisions, as well as start/continue/stop decisions, following pre-set guidelines.
• Actively stop or kill initiatives that do not demonstrate clear value, adoption potential, or strategic fit.
• Participate regularly in client conversations to better understand client needs.
• Act as primary interface and product sponsor to product managers, e.g., help get funding, set requirements, mobilize business SME involvement, anything needed to deliver at pace.
• Redesign end‑to‑end Asset Management delivery workflows to embed digital and AI where they materially improve outcomes.
• Work with Service Line leadership to support adjustments to new ways of working.
• Build a local network of digital & AI champions (change agents and catalysts) within each Service Area Group.
• Strengthen foundational digital skills and AI usage within the organization (e.g., Drive Citizen Development participation, measure and steer on AI usage, make part of SPO).
• Setup adoption campaigns around new tooling / digital products, and ways of working, incl. training programs and updated global procedures.
• Turn global data strategy into an actionable plan within the service line, with clear focus around the priority areas (digital must-wins).
• Create knowledge and data libraries around discipline areas, managed within Communities of Practice.
• Setup data governance (who collects, who structures and maintains) and measure adherence and progress.
• Define any other pre-requisites for digital innovation and bake into transformation plan.
• Own the Asset Management Digital and AI innovation backlog and roadmap, in partnership with Digital Intelligence, ensuring alignment to strategic priorities and measurable value delivery.
• Drive investment prioritisation and portfolio transparency within the Innovation governance framework, enabling clear decision-making and optimal allocation of resources.
• Champion digital adoption across the Asset Management workforce and project delivery, working closely with Services leadership to embed tools, behaviours, and ways of working that maximise impact.

Digital & AI Transformation Director – Asset Management

• Set the Digital & AI direction for the Service Line
• Create an Architecture + Urbanismspecific digital & AI strategy in the context of our 3yr-out vision and strategy of the Architecture + Urbanism, and the strategic priorities of Industries & Sectors.
• Define and regularly update “digital must-win” areas by conducting competitor analyses and gap analysis within existing portfolio of tools and digital products and partnerships.
• Identify which Architecture + Urbanism delivery domains and workflows must be redesigned.
• Setup collaboration rhythm with Digital Intelligence, Investment governance, pipeline management approach and prioritization framework, change network, CoPs, etc.
• Set clear objectives for the transformation that link to overall Architecture + Urbanism performance metrics.
• Own the Opportunity Portfolio
• Collect and pro-actively source digital opportunities and use cases within the organization, in close collaboration with peers in other Service Lines and Industries.
• Kick-start and actively participate in AI studios around the most promising opportunities, to quickly validate and potentially prototype, ideally in real client settings.
• Work closely together with Digital Intelligence counterparts to make buy/build/partner decisions, as well as start/continue/stop decisions, following pre-set guidelines.
• Actively stop or kill initiatives that do not demonstrate clear value, adoption potential, or strategic fit.
• Participate regularly in client conversations to better understand client needs.
• Act as primary interface and product sponsor to product managers, e.g., help get funding, set requirements, mobilize business SME involvement, anything needed to deliver at pace.
• Rewire Service Delivery workflows
• Redesign end-to-end Architecture + Urbanism delivery workflows to embed digital and AI where they materially improve outcomes.
• Work with Service Line leadership to support adjustments to new ways of working.
• Embed Digital & AI in our capabilities and drive adoption
• Build a local network of digital & AI champions (change agents and catalysts) within each Service Area Group.
• Strengthen foundational digital skills and AI usage within the organization (e.g., Drive Citizen Development participation, measure and steer on AI usage, make part of SPO)
• Setup adoption campaigns around new tooling / digital products, and ways of working, incl. training programs and updated global procedures.
• Strengthen data foundations and other boundary conditions
• Turn global data strategy into an actionable plan within the service line, with clear focus around the priority areas (digital must-wins).
• Create knowledge and data libraries around discipline areas, managed within Communities of Practice.
• Setup data governance (who collects, who structures and maintains) and measure adherence and progress.
• Define any other pre-requisites for digital innovation and bake into transformation plan.
• Own the Architecture + Urbanism Digital and AI innovation backlog and roadmap, in partnership with Digital Intelligence, ensuring alignment to strategic priorities and measurable value delivery.
• Drive investment prioritisation and portfolio transparency within the Innovation governance framework, enabling clear decision-making and optimal allocation of resources.
• Champion digital adoption across the Architecture + Urbanism workforce and project delivery, working closely with Services leadership to embed tools, behaviours, and ways of working that maximise impact.

Digital & AI Transformation Director – Architecture, Urbanism

• Set the Digital & AI direction for the Service Line
• Create an Environmental Services specific Digital & AI strategy
• Define and regularly update "digital must-win" areas
• Identify which Environmental Services delivery domains and workflows must be redesigned
• Setup collaboration rhythm with Digital Intelligence
• Set clear objectives for the transformation
• Own the Opportunity Portfolio
• Collect and pro-actively source digital opportunities and use cases
• Kick-start and participate in AI studios
• Work closely with Digital Intelligence counterparts
• Actively stop or kill initiatives that do not demonstrate clear value
• Participate regularly in client conversations
• Act as primary interface and product sponsor
• Redesign end-to-end Environmental Services delivery workflows
• Embed digital and AI where they materially improve outcomes
• Build a local network of digital & AI champions
• Strengthen foundational digital skills and AI usage
• Setup adoption campaigns around new tooling
• Turn global data strategy into an actionable plan
• Create knowledge and data libraries
• Setup data governance and measure adherence and progress
• Own the Environmental Services Digital and AI innovation backlog and roadmap
• Drive investment prioritisation and portfolio transparency
• Champion digital adoption across the Environmental Services workforce

Digital & AI Transformation Director, Environmental Services

• Lead the design and delivery of advanced analytics, visualization, and AI solutions for global clients
• Develop interactive dashboards and insights using Power BI, Tableau, and Looker Studio
• Architect and oversee data integrations and migrations across platforms such as EQuIS, Enablon, and modern cloud environments (Azure, AWS, GCP)
• Design and maintain scalable data pipelines using SQL, Python, and ETL frameworks
• Partner with clients to define data models, governance frameworks, data quality, and security standards
• Design and implement agentic AI workflows and AI-enabled use cases supporting EHS&S and sustainability objectives
• Support environmental data analysis across groundwater, surface water, air quality, and biological metrics
• Act as a trusted advisor to senior client stakeholders, translating business strategy into digital solutions
• Contribute to practice development, internal knowledge sharing, and innovation initiatives

Principal Consultant – Global AI, Data Services

• Build, test, and deploy automation, monitoring, and analysis solutions for agent workflows
• Support deployment and scaling of automated agent-based solutions across development and production environments
• Investigate technical, operational, and reliability issues during development and implementation
• Build and integrate software tools that improve system reliability, observability, and scalability
• Support setup of development and production environments, including deployment-related activities
• Develop best practices and methodologies for provisioning, configuration management, monitoring, and troubleshooting
• Collaborate with delivery teams to define and track service level indicators, service level objectives, SLAs, and error budgets
• Create and recommend process improvements that increase stability, efficiency, and operational readiness
• Contribute to the ongoing improvement of operational processes for automated agent workflows

Senior Artificial Intelligence Operations Specialist

• Investigate the latest LLM MLM models and evaluate and compare accuracy and efficiency for our in-domain use cases
• Develop tools and processes to create data pipelines for ML training and customization
• Finetune LLMs for the healthcare domain
• Help develop and productionize machine learning (ML) solutions leveraging our customized models in the fields of Document understanding, Search and QnA, GenAI, Virtual Agents, etc.
• Work across the complete lifecycle of ML model development, including problem definition, data exploration, feature engineering, model training, validation, and deployment.
• Participate in code reviews, testing, and quality assurance processes.
• Troubleshoot and resolve technical issues related to AI model, integration, deployment and backend services.
• Document and communicate research and development processes, and architectural decisions.
• Ensure the security and compliance of healthcare data, adhering to HIPAA regulations.

Senior Applied AI/ML Scientist

• Lead enterprise AI adoption across all functions, moving from pilots to measurable, scaled deployment
• Operationalize the company’s AI operating model, coordinating ideation through production across teams
• Drive and govern the Functional Certification Program, including SLA adherence and recertification cadence
• Convert unsanctioned “shadow AI” into approved, governed, and measurable enterprise usage
• Define, track, and report AI performance metrics including efficiency, cost, revenue impact, and productivity gains
• Establish Digital Realty as a “Customer Zero” reference for AI deployed on its own infrastructure
• Translate internal AI maturity into external market positioning with Product, Marketing, and Sales leadership
• Engage directly with strategic customers and partners as a senior technical and commercial AI leader
• Shape the company’s point of view on AI infrastructure and differentiation in the market
• Represent Digital Realty externally through industry events, analyst briefings, and executive engagements

VP, AI Acceleration

• 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

• Build and scale enterprise AI and machine learning capabilities across supply chain functions including logistics, distribution, planning, sourcing, and labor.
• Translate business problems into well-defined AI use cases, with clear success metrics and operational outcomes.
• Define and operationalize standard frameworks for AI use-case intake, prioritization, development, deployment, and lifecycle management.
• Lead the end-to-end delivery of ML-driven solutions, from problem framing and model development through production deployment and adoption tracking.
• Own and continuously evolve the Supply Chain Data Science & AI roadmap, aligned with business priorities, AOP commitments, and long-term capability goals.
• Partner with data engineering, BI, and IT teams to embed AI solutions into dashboards, workflows, and operating processes, not standalone models.
• Lead AI solution design using Microsoft technologies, including Azure AI, Azure Foundry, Copilot, and Power Platform.
• Drive adoption of GenAI, copilots, and AI agents in a secure, scalable, and governed manner.
• Evaluate, pilot, and integrate external AI tools and vendors, ensuring fit with enterprise data architecture, security standards, and long-term scalability.
• Establish best practices for model development, deployment, monitoring, explainability, and reuse, enabling repeatable delivery.
• Mentor and develop analysts and data scientists, raising overall AI maturity and execution rigor across the organization.
• Communicate progress, risks, and outcomes to senior stakeholders using clear, business-focused language.

Senior Manager, Analytics & AI

• Define and drive the enterprise AI enablement strategy and roadmap for OCTO and HPE Labs, aligned to HPE business priorities.
• Act as a hands on Distinguished Technologist: set architecture, patterns, and best practices for AI/ML systems; contribute to prototypes and complex implementations; and validate designs for scale, resilience, and security.
• Lead research transition: collaborate with HPE Labs to mature innovations into production-ready components and repeatable delivery patterns.
• Establish and enforce governance: model validation and evaluation standards, ethical/ responsible AI guardrails, data privacy/compliance, and risk management practices across AI initiatives.
• Build, mentor, and grow a high performing team of applied AI engineers and data scientists; nurture technical leadership and cross functional collaboration.
• Partner broadly across product, engineering, security, legal, data engineering, and field teams to operationalize AI use cases and maximize reuse across HPE.
• Measure and communicate impact: define KPIs for adoption, ROI, model performance, reliability, and operational cost; report progress to OCTO, HPE Labs and senior leadership.
• Represent HPE externally: engage customers, partners and the technical community to evangelize HPE’s AI enablement approach and gather field feedback that shapes the roadmap.

Distinguished Technologist – Director, AI Strategy and Enablement

• Develop production-grade integration and automation solutions: Design and implement production-ready automation workflows that integrate cloud services, internal data sources, and LLM endpoints.
• Lead the development and deployment of domain-specific LLMs: Fine-tune lightweight models on internal data from Gong, Notion, BigQuery, and other sources, then make them accessible to teams across the organisation through intuitive interfaces.
• Establish best practices and patterns for AI and automation across the company: Create templates, documentation, and training materials that enable non-technical teams to build and deploy their own automation workflows confidently.
• Enable widespread adoption: Run hands-on workshops, provide ongoing support, and mentor teammates so anyone at UpGuard can leverage AI and automation tools effectively.
• Embed security & governance: Bake privacy, compliance, and cost controls into every workflow and model deployment, ensuring enterprise-grade reliability and data protection.

AI and Automation Engineer

• Develop and maintain core School of Splunk Field Sales Enablement portfolio
• Design and deliver AI-focused onboarding and upskilling curricula
• Integrate critical technical sales skills into curriculum for learners to develop mastery
• Compose test questions, evaluations, and assessments that validate proficiency
• Develop and continuously refresh learning content that reflects the messaging and positioning related to Splunk platform
• Work with key stakeholders to develop technical seller training programs
• Serve as a trusted advisor to technical sales stakeholders and SMEs
• Update and optimize existing GFE training assets to reflect Cisco's current strategic direction

Curriculum Designer – AI Native

• Lead the design of robust cloud infrastructure and operationalization of Large Language Models (LLMs)
• Build and maintain Enterprise Feature Stores and real-time data lakes (BigQuery, Pub/Sub)
• Design and implement resilient, secure multi-cloud architectures (GCP and Azure) using Terraform (IaC)
• Operationalize ML models using Python, PySpark, and Kafka for both batch and real-time inference
• Implement end-to-end CI/CD pipelines for automated model training, deployment, and seamless rollback capabilities
• Collaborate with data scientists to understand model objectives and translate them into technical specifications
• Deploy AI models into multiple environments using CI/CD pipelines
• Establish strong observability and data governance using tools like Grafana, OpenTelemetry, Splunk or Arize
• Create and maintain comprehensive documentation for infrastructure setups, model development processes, and deployment workflows

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