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 - New England. 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 $286,450 - 370,700, which includes base salary and commissions. 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 What your day-to-day work as a Sr. AI Engineer looks like: - Create solutions for customers: Architect and implement intelligent LLM-powered ETL pipelines from scratch to transform unstructured client data into concrete, structured solutions. - Build individual agents: Develop autonomous, multi-agent systems using state-of-the-art frameworks to automate complex, multi-step human business processes. - Keep the quality high: Design and maintain robust evaluation frameworks to systematically quantify AI performance and serve as the gatekeeper of quality for production systems. - Own the whole cycle: Build and deploy high-performance RAG systems and wrap the AI logic into performant, production-ready microservices (e.g., FastAPI). - Grow with your team: Actively engage in creative brainstorming sessions and technical design discussions with teammates to challenge assumptions, jointly solve problems, and grow the team's collective knowledge. Qualifications - Fluent English: we're an English-only company. - 2+ years of professional working experience as an engineer (5+ years gets you closer to the "senior" bar). - Strong Python: at least 2 years of real, daily use. - Hands-on LLM experience: ideally 1–3 years of actually shipping LLM-powered features (not just notebooks). - Experience building AI workflows / Agents: multi-step, multi-agent, or otherwise non-trivial orchestration. - RAG systems in production: you've designed retrieval, evaluated it, and made it fast and reliable. - Shipped to real customers: you've built things that real, paying users actually use. Side-project demos don't count here. - Good communicator: happy in async text (Slack) and on calls. You don't disappear for a week into a branch. - Genuinely curious about AI: you can talk us through a recent paper, model, or architectural shift that changed how you think about building systems, and why it mattered to you. - Bonus: you have a cat. (Optional. We don't discriminate against dog people. Much.) Benefits - Remote work: Work from home or wherever you like; we are a 100% remote company. - Flexible working hours: Work when you feel it. It's your life. - Challenging projects: Work on challenging projects with meaningful impact for our customers. - Amazing, creative team: Supportive, curious, open-minded. We joke around a lot but we're serious about the quality of our work. - Continuous learning budget: We pay for your experiments and your side quests. - Enthusiastic AI Engineers: We share a deep passion for tech and AI. We love to learn, grow our skills, and have fun while doing it. - Fault-tolerant culture: Mistakes are part of learning. We make them, we learn, we move on. No blaming, no negative feelings — maybe a few jokes. - ...and yes, you do get a Claude Code subscription.

• Design the end-to-end architecture of the conversational agent using: LLMs, RAG, tool-calling, orchestration, guardrails. • Build and deploy AI services using Python and FastAPI. • Design secure and resilient integrations with: core systems, Salesforce or similar, APIs, cloud services. • Define strategies for: context engineering, retrieval, embeddings, AI observability. • Implement best practices for resilience, security, and troubleshooting. • Collaborate with Backend, Cloud, Architecture, and Product teams. • Lead technical standards, code reviews, and architecture documentation.

• Liderar la definición técnica, arquitectura e implementación de capacidades de Inteligencia Artificial. • Diseñar la arquitectura AI/LLM del proyecto alineada con estándares enterprise. • Liderar la implementación de servicios AI utilizando Python y frameworks modernos. • Diseñar integraciones seguras y resilientes entre modelos AI, APIs y sistemas enterprise. • Definir estrategias de Prompting Retrieval Embeddings Orchestration Observabilidad AI. • Guiar decisiones de performance, escalabilidad y optimización de costos en workloads AI. • Diseñar pipelines AI y flujos de inferencia sobre GCP. • Implementar APIs y servicios AI utilizando Python/FastAPI. • Liderar troubleshooting relacionado con respuestas, latencia, calidad y observabilidad de modelos. • Colaborar con equipos Backend, Frontend, Cloud y Arquitectura. • Definir estándares técnicos, realizar code reviews y promover buenas prácticas de AI Engineering. • Documentar arquitectura, ADRs y decisiones técnicas vinculadas a AI.