Role Description Within the Forward Deployment Engineering (FDE) Unit, the Advisory AI Architect is a hands-on technical leader who designs and builds AI and GenAI solutions with customers. You will own key parts of the AI software stack, drive rapid proof-of-value sprints, and help move AI workloads toward stable production on Dell infrastructure, balancing speed, reliability, security, and responsible AI practices. You focus on fit-for-purpose architectures and enablement so customers can operate and extend their AI solutions after FDE Units disengage. Join us to do the best work of your career and make a profound social impact as an Advisory AI Architect on our Forward Deployment Engineering (FDE) Team in Remote - Austin, Texas (Central / West). What You’ll Achieve - Design scalable AI architectures for customer use cases in line with enterprise and security standards - Lead implementation of AI software components such as model serving, orchestration, retrieval, and integrations - Run time-bound proofs of value to demonstrate business outcomes quickly and clearly - Help migrate AI workloads between cloud, on-premises, and hybrid environments on Dell infrastructure - Enable customer engineers and platform teams to support and extend solutions after handover You Will: - Design, configure, and implement AI solution stacks, including model serving, orchestration, retrieval pipelines, vector stores, and related components - Select practical tools and patterns to avoid tooling sprawl and deliver working prototypes and PoVs tied to clear success measures - Lead PoV sprints (typically a few weeks): refine scope, build and iterate on solutions, and present outcomes and recommendations to stakeholders - Plan and execute cloud-to-on-prem and hybrid migration patterns for AI workloads onto Dell infrastructure, optimizing performance, reliability, and security - Take shared responsibility for production readiness and early production stability, including monitoring, performance optimization, and issue triage - Work closely with AI Data Specialists to define and consume AI-ready data pipelines that support performance and reliability - Collaborate with AI Strategists and Enterprise Architects to align technical scope with business outcomes and target-state architectures - Provide documentation, runbooks, and knowledge transfer to customer teams, and contribute to Dell AI Factory reference architectures and playbooks - Mentor other technical team members on AI architecture patterns, Dell AI infrastructure capabilities, and responsible AI practices Qualifications - Typically, 6+ years in enterprise architecture, AI/ML platforms, or systems engineering, delivering production workloads in large enterprises - Hands-on experience designing and implementing AI solution components such as model serving, orchestration, retrieval pipelines, vector stores, and integrations - Strong foundation in modern software engineering practices (e.g., CI/CD, automated testing, observability, DevOps/SRE, infrastructure-as-code) - Experience delivering and operating production AI or other large-scale distributed systems in enterprise environments - Demonstrated ownership of production systems, including stabilization and performance tuning in high-visibility contexts - Ability to explain complex technical trade-offs and architectures in clear language for both technical and non-technical stakeholders - Ability to travel to customer sites and Dell locations as needed, in line with business requirements and applicable laws and Dell policies Desirable Requirements - Bachelor’s degree in computer science, Engineering, Data Science, or a related field. - Experience deploying AI solutions across cloud, on-premises, and hybrid environments. - Familiarity with AI security, privacy, and governance and modern cloud / data / ML tooling (e.g., major public clouds, Kubernetes). - Hands-on experience with GenAI or RAG-style solutions and leading small technical teams in customer-facing projects. Compensation Dell is committed to fair and equitable compensation practices. The Total Target Compensation range for this position is $249,050 - 322,300, which includes base salary and commissions. Benefits - Your life. Your health. Supported by your benefits. You can explore the overall benefits experience that awaits you as a Dell Technologies team member — right now at MyWellatDell.com Company Description We believe that each of us has the power to make an impact. That’s why we put our team members at the center of everything we do. If you’re looking for an opportunity to grow your career with some of the best minds and most advanced tech in the industry, we’re looking for you. Dell Technologies is a unique family of businesses that helps individuals and organizations transform how they work, live and play. Join us to build a future that works for everyone because Progress Takes All of Us. Dell Technologies is committed to the principle of equal employment opportunity for all employees and to providing employees with a work environment free of discrimination and harassment.

Role Description GuidePoint Security is seeking an Applied AI Engineer to join our AI and Agentic Enablement practice. This is a mid-level engineering role for practitioners with hands-on experience designing and deploying agentic systems. The role spans harness development within existing agentic platforms, internal tooling for NE regional teams, and structured enablement programs that build lasting agentic capability across the organization. Working independently across the full delivery lifecycle, this engineer leads harness design and deployment, owns internal tooling initiatives, and drives the enablement programs that transfer agentic operating capability to regional teams. Roles and Responsibilities: - Design, build, and deploy agentic harnesses and LLM-integrated workflows from prototype through production within existing platforms. - Define and own performance benchmarks to evaluate reliability, accuracy, and continuous improvement of agentic pipelines. - Evaluate and recommend emerging AI tools, models, and platforms for adoption. - Identify, develop, and maintain AI-powered automations and tools that improve efficiency across service delivery, operations, and sales functions throughout the Northeast region. - Lead workflow assessments to identify opportunities for agentic automation and design repeatable, scalable delivery frameworks. - Own documentation, testing, and iteration on productized AI components and proof-of-concept builds for internal and client audiences. - Design and deliver enablement programs that build regional teams' capability to independently operate, maintain, and extend agentic harnesses. - Develop training materials and lead workshops that build agentic AI literacy across functional teams, including handoff documentation and runbooks. - Other duties as assigned. Qualifications - B.S. degree in computer science or relevant field and 3 years of experience or M.S. degree. - 3+ years of software development or AI/ML engineering experience. - Demonstrated ability to design, author, and deploy agentic harnesses within existing agentic platforms. - Working knowledge of Python and at least one additional language relevant to agentic development. - Working understanding of large language models, prompt engineering, and API-based AI integration. - Ability to independently scope, build, and ship agentic solutions at a mid-level engineering standard, ensuring secure development practices throughout. - Demonstrated ability to explain technical concepts to non-technical audiences. Requirements - Experience with cloud platforms (AWS, Azure, or Google Cloud), particularly AI/ML services. - Experience with vector databases, orchestration layers, or workflow automation platforms. - Experience with retrieval-augmented generation (RAG) patterns or tool-use/function-calling with LLMs. - Experience designing and applying evaluation frameworks and benchmarks for AI systems. - Experience designing and facilitating technical enablement programs for mixed audiences. Travel Requirements - Up to 10% travel. Physical Requirements - Sedentary work. - Substantial movement of the wrists, hands, and/or fingers for a minimum of 8 hours a day. - Required to have close visual acuity to view computer terminal and/or extensive reading for a minimum of 8 hours a day. Benefits - Remote workforce primarily (U.S. based only, some travel may be required for certain positions, working on-site may be required for Federal positions). - Group Medical Insurance options: Zero Deductible PPO Plan (GuidePoint pays 90% of the premium for employees and 70% for family plans) or High Deductible Health Plan with HSA (GuidePoint pays 100% of the employees premiums and 75% for family plans). - Group Dental Insurance: GuidePoint pays 100% of the premium for employees and 75% of family plans. - 12 corporate holidays and a Flexible Time Off (FTO) program. - Healthy mobile phone and home internet allowance. - Eligibility for retirement plan after 2 months at open enrollment. - Pet Benefit Option.

• Build and maintain shared infrastructure: secure web app hosting infrastructure, MCP/API standards, secret/key management, model selection, guardrails, and a centralized pattern library that all builders across the organization can pull from. • Own the review, tracking, and advisory process for all corporate AI and automation builds — MCP servers and tool configurations, Claude Skills, API integrations, and agentic workflows — before deployment. • Partner directly with AI specialists across departments to identify, scope, and build AI and automation solutions that meet high standards for cost, security, and scalability security before they ship. • Define and maintain the secure intake path for AI and automation requests across the organization, replacing ad-hoc builds and shadow IT with a governed, cost-effective, and scalable process. • Contribute to the organization’s AI cost efficiency by monitoring, alerting, and setting thresholds on AI spend across usage-based tools and platforms.

• Work closely with business stakeholders to rapidly develop, demonstrate, and refine AI solutions. • Take a hands-on engineering approach focused on building rather than advising. • Work directly with the client to translate business problems into AI-enabled prototypes and production-ready solutions.