Role Description This role has been designated as ‘Remote/Teleworker’, which means you will primarily work from home. Global Sales at HPE is about building the future. We are redefining what’s next and combining our legacy of innovation with a bold new goal to accelerate everything we do. Our sales organization is comprised of 10,000+ professionals in sales, presales, service, and support functions. Together with our partners, we deliver global, commercial, public sector & small/medium business customers throughout 11 geographies. We’re transforming businesses. Join us redefine what’s next for you. What you’ll do: - Strong demonstrated background deploying and configuring enterprise Kubernetes (Rancher RKE2, Red Hat OpenShift, CNCF Kubernetes) - microk8s and kubespray should not be considered demonstrated background. - Familiarity with SLURM on Kubernetes frameworks (Slinky, SUNK, etc.). - Strong demonstrated background working with Ansible automation frameworks. - Familiarity with leveraging REST APIs for product integrations. - Familiarity with HPC architectures, network topologies, and high performance storage platforms. - Knowledge of NVIDIA's AI Enterprise tools, specifically BCM and DCGM for deploying and managing. Architecture leadership - Lead end-to-end architecture design for sovereign AI deployments, ensuring compliance with data residency, privacy, and regulatory requirements. - Develop scalable, secure, and robust AI/ML reference architectures, including model lifecycle management, data pipelines, inference infrastructure, and governance frameworks. - Evaluate and select technologies, cloud/on-prem infrastructure, and tooling aligned to sovereign and risk-management constraints. - Provide architectural oversight across implementation teams, ensuring alignment with enterprise standards and risk mitigation strategies. Risk management and governance - Identify, assess, and manage risks across the AI solution lifecycle. - Develop and implement governance frameworks that embed responsible AI principles, auditability, and continuous risk monitoring. - Partner with security, compliance, and legal teams to ensure adherence to sovereignty mandates and enterprise risk frameworks. - Embed security-by-design and risk-by-design in architecture, deployment, and operations. Technical execution - Create architectural documentation, diagrams, and governance frameworks for AI model development, deployment, and monitoring. - Drive security-by-design principles into all AI components, including encryption, access control, auditing, and safe model operation. - Partner with engineering, security, compliance, and product teams to ensure architectural integrity throughout execution. - Lead technical reviews and guide the resolution of architectural and integration issues. Customer engagement and stakeholder management - Serve as a trusted advisor to customers—C-suite, technical leaders, and regulatory stakeholders, helping them shape their sovereign AI strategy, facilitating design workshops, discovery sessions and technical deep-dives. - Translate complex customer requirements into actionable architectures and solution roadmaps. - Communicate architectural decisions and recommendations to executives, delivery teams, security, product engineers, and customers. - Maintain tight alignment with multiple internal functions within HPE. Sovereign AI Thought Leadership - Stay ahead of global developments in sovereign AI, regulation, digital sovereignty trends, and AI risk management. - Contribute to thought leadership initiatives through whitepapers, presentations, and technical guidance. - Serve as an ambassador for architectural excellence across geographies, ensuring alignment and knowledge sharing across regional teams. - Mentor, coach, and develop solution and enterprise architects—building capability, consistency, and technical depth across locations. Qualifications - 10+ years’ experience in enterprise sales or sales leadership within IT services, cloud, AI/ML, or data/analytics domains. - 5+ years hands-on Linux experience. Requirements - Strong grounding in data architecture, ML lifecycle, cloud platforms (AWS/Azure/GCP/Greenlake), MLOps tooling, security/privacy frameworks, APIs/integration patterns, with the ability to translate technical concepts into business value. - Proven experience selling complex technology solutions to enterprise and/or public sector organizations. - Demonstrated ability to influence teams without direct authority across GEOs, business units, and matrix environments. - Exceptional communication skills with the ability to translate technology into business value. Benefits - Health & Wellbeing: We strive to provide our team members and their loved ones with a comprehensive suite of benefits that supports their physical, financial and emotional wellbeing. - Personal & Professional Development: We invest in your career because the better you are, the better we all are. We have specific programs catered to helping you reach any career goals you have. - Unconditional Inclusion: We are unconditionally inclusive in the way we work and celebrate individual uniqueness.

Role Description The AI/ML Practice Architect is a senior, hands-on technical leader who combines solution architecture and customer consultation with deep applied AI/ML engineering capability. This role accelerates practice growth by shaping repeatable offerings, guiding delivery excellence, and building production-grade AI systems — especially GenAI/LLM, retrieval, evaluation, and agentic workflows — integrated into customer platforms. This role will travel as needed, which includes customer onsite workshops, executive presentations, delivery kickoffs, and internal practice events. Why This Role Exists - Drive measurable customer outcomes by designing and delivering AI/ML and GenAI solutions end-to-end (discovery → build → deploy → operate). - Scale TGS AI capabilities through reusable playbooks, reference architectures, accelerators, and enablement. - Partner with Sales and Delivery to shape, price, and win work; serve as a trusted advisor in pre- and post-sales engagements. Key Outcomes (First 6–12 Months) - Establish (or evolve) the AI/ML Solution Playbook: discovery templates, context/RAG patterns, evaluation rubrics, and governance/guardrails. - Deliver 2–4 production deployments (or major releases) demonstrating reliability, safety, and business value; publish reusable artifacts to the practice repository. - Create a reference architecture for agentic AI/LLM systems (tool use, memory, orchestration, human-in-the-loop controls, observability). - Improve delivery predictability: clear estimation models, quality gates, and SDLC/MLOps/LLMOps standards aligned to DevOps principles. - Support GTM: contribute to proposals, SOWs, pricing, case studies, demos, and executive narratives that help land-and-expand accounts. Core Responsibilities - Practice Architecture & Consulting (Customer Value + Growth): - Lead customer discovery and value definition: map current/future-state workflows, define success metrics, and translate business goals into technical requirements. - Design solution architectures and delivery approaches; document assumptions, risks, dependencies, and cost/effort estimates. - Create and maintain practice solution content: reference architectures, accelerators, templates, delivery playbooks, and pricing guidance. - Partner with Sales, Solutioning, Delivery Leadership, and Practice Directors on pre-sales strategy, proposals, and executive communications. - Mentor consultants/engineers: design reviews, technical coaching, and best-practice enablement across engagements. - Continuously optimize delivery processes, promote reuse, and champion innovation rooted in measurable customer impact. - AI/ML Engineering & Delivery (Hands-on Technical Leadership): - Build and ship production AI/ML systems including model integration, data pipelines, services, and user experiences. - Design and implement GenAI/LLM solutions: prompt & context engineering, RAG grounding, embedding/vector store strategies, and latency/quality trade-offs. - Evolve prompted workflows into agentic AI: durable execution, tool use, memory, orchestration (single- and multi-agent), and human-in-the-loop gates. - Establish evaluation and experimentation rigor: offline/online tests, human + AI evaluation rubrics, error taxonomies, and KPI instrumentation. - Implement security, safety, and compliance controls: PII handling, prompt-injection mitigations, model risk management, and red-teaming. - Operationalize MLOps/LLMOps: CI/CD, model/version management, observability, drift/feedback loops, and incident response. - Leadership, Accountability & Cross-Functional Influence: - Drive execution cadence with clear gates, owners, and KPIs from discovery through launch. - Hold self and others accountable to commitments; proactively resolve issues before they impact customers. - Communicate trade-offs, impact, and risk to technical and non-technical stakeholders; produce executive-ready narratives and artifacts. - Support practice hiring/interviewing and capability building as needed; contribute to internal communities of practice. Qualifications - 8 or more years in full stack software engineering, data engineering, ML engineering, or applied AI, including delivery in customer-facing or consulting environments. - 3 or more years building and deploying ML/LLM/GenAI-powered products (e.g., prompt/context engineering, RAG, evaluation, and guardrails). - Strong solution architecture skills: requirements gathering, estimation, system design, and leading technical decisions across teams. - Proficiency in Python and at least one of: TypeScript/JavaScript, Java, Go, or Rust; experience building APIs and services (e.g., FastAPI, Django, Node/Express). - Experience with cloud platforms (AWS, Azure, or GCP) and containerization (Docker); familiarity with Kubernetes is a plus. - Ability to influence across stakeholders (Sales, Delivery, Engineering, Product, Security/Privacy) and communicate effectively at multiple levels. Preferred Qualifications - Experience deploying or fine-tuning open-source LLMs (e.g., Hugging Face, vLLM, Ollama) and/or using managed services (e.g., Azure OpenAI, Bedrock, Vertex AI). - Hands-on experience with agent frameworks/orchestration (e.g., LangGraph, AutoGen, CrewAI) and tool integration patterns. - Experience with vector databases and semantic search (e.g., Pinecone, Weaviate, Chroma) and advanced RAG/knowledge graph techniques. - Experience leading small teams or technical workstreams while remaining hands-on. - Exposure to regulated environments (e.g., Finance & Healthcare) and formal security/privacy review processes. Success Profile (Competencies & Behaviors) - Manages Complexity: Integrates diverse inputs, clarifies ambiguity, and translates business and technical constraints into actionable architecture and delivery plans. - Customer Focus: Builds trusted relationships, aligns to measurable outcomes, and delivers customer-centric solutions with quantified impact. - Communicates Effectively: Delivers clear multimode communication; explains trade-offs, risks, and “the why” behind decisions to technical and non-technical audiences. - Ensures Accountability: Owns outcomes, meets commitments, escalates early, and drives execution to closure. - Cultivates Innovation: Creates new and better ways for the organization to be successful; promotes reuse and continuous improvement. - Optimizes Work Processes: Designs efficient delivery processes; improves quality through automation, standards, and playbooks. - Nimble Learning / Self-Development: Learns through experimentation, seeks feedback, and stays current with AI/ML and GenAI trends. - Collaborates: Builds partnerships across Sales, Delivery, Engineering, and customer teams to meet shared objectives. - Decision Quality: Makes good and timely decisions using decision criteria, trade-offs, and risk mitigation. - Manages Ambiguity / Situational Adaptability: Operates effectively when the path is unclear; adapts approach to shifting constraints and stakeholder needs. - Drives Results: Consistently delivers results under tough circumstances and focuses on key goals during setbacks. Job Type & Location This is a Permanent position based out of Chicago, IL. Pay and Benefits The pay range for this position is $136,000.00 - $204,000.00/yr. We reserve the right to pay above or below the posted wage based on factors unrelated to sex, race, or any other protected classification. - Medical, Dental, and Vision - Critical Illness, Accident, and Hospital - 401(k) Retirement Plan – Pre-tax and Roth post-tax contributions available - Life Insurance (Voluntary Life and AD&D for employee and dependents) - Short and Long-Term Disability - Health Spending Account (HSA) - Transportation Benefits - Employee Assistance Program - Time Off/Leave (PTO, Vacation or Sick Leave) Workplace Type This is a fully remote position. Application Deadline This position is anticipated to close on Jun 12, 2026.

• Define and maintain the business architecture, capability roadmap, and solution vision for global service scheduling systems, aligned with enterprise and Commercial Operations strategies. • Partner with business process owners, regional service leaders, and cross‑functional stakeholders to design scheduling solutions that enhance both customer experience and operational performance. • Lead the business design and delivery of scheduling system initiatives, including requirements definition, solution design, testing, deployment, and post‑release stabilization. • Drive the transformation from manual and high‑touch scheduling to digital, automated, and self‑service experiences for customers and internal users. • Translate complex business needs into clear, prioritized functional and architectural designs for IT delivery teams. • Collaborate closely with IT teams, system integrators, and software vendors to ensure solutions meet business, architectural, and scalability requirements. • Support prioritization of system enhancements and defect resolution to balance operational stability with strategic capability development. • Coordinate implementation, testing, training, and change management activities to ensure successful adoption across global service organizations. • Partner with analytics and data teams to define reporting and insight requirements that support scheduling optimization and performance management. • Communicate plans, progress, and outcomes effectively to senior stakeholders, including executive‑level audiences.

Role Description En Experis Argentina nos encontramos en la búsqueda de nuestro Microsoft 365 Messaging Architect (Exchange Hybrid) para importante Compañía del rubro de Telecomunicaciones. Vas a trabajar en: - Diseño de arquitectura de mensajería en AWS. - Migración y coexistencia hacia Microsoft 365. - Seguridad de correo (Proofpoint). - Integraciones y automatización. - Proyectos estratégicos de modernización IT. Qualifications - Experiencia sólida en Exchange On-Prem (2019+) y arquitecturas híbridas. - Experiencia en Exchange Online (O365) y migraciones. - Conocimientos en infraestructura (AD, Networking, Seguridad, Certificados). - Seguridad en mensajería (SPF, DKIM, DMARC, Anti-Spam, Anti-Phishing). - Automatización con PowerShell / IaC. - Experiencia en AWS y/o Azure. - Inglés avanzado (Excluyente). Requirements - Jornada de trabajo: Full Time 9am – 6pm. - Modalidad de trabajo: Remoto. - Contrato: Por tiempo indeterminado, con Experis. Benefits - Salario: A convenir. - Prepaga individual. - Plataforma gratuita de capacitaciones. - Descuento 45% en Educación IT. - 75% en Open English. - 20% en instituto de idiomas CUI. - 50% Megatlon. - Descuentos Cuponstar y supermercados, entre otros.