We move quickly toward the work that matters most. We reward experimentation, encourage bold thinking, and remove unnecessary barriers so great ideas can become reality faster. Our teams embrace a customer-first, first-to-market mindset, transforming rapid feedback into better products and better outcomes. We aren't looking for people who are content with the status quo- we look for builders who question it, improve it, and occasionally rewrite it.
If you're energized by solving complex systems challenges, excited to work alongside AI to amplify your impact, and motivated by the opportunity to shape what's next instead of simply maintaining what's been done before, you'll find your place here.
Join us and help build the future of enterprise technology
What you'll achieve
As an Agentic Context Engineering Architect & AI Practitioner, you will be responsible for designing, building, and operating the enterprise AI Harness and context engineering frameworks to enable secure, scalable, and governable AI-assisted software development . You will work with cross-functional engineering, architecture, product, security, and infrastructure teams on cutting-edge AI agent workflows, retrieval architectures, and developer platform integrations .
You will
Design, build/code/implement, and operate the enterprise AI Harness that enables secure, scalable, and governable AI-assisted software development across engineering organizations
Develop and manage context engineering frameworks that optimize how agents acquire, interpret, retrieve, and utilize information throughout the software development lifecycle
Architect and maintain context management services, including knowledge ingestion, context assembly, retrieval mechanisms, metadata management, and lifecycle governance for AI agent workflows
Design and implement agent memory frameworks, including short-term, long-term, session-based, and persistent memory patterns that improve agent effectiveness, consistency, and task completion accuracy
Build and maintain shared services, reusable frameworks, developer tooling, and platform integrations that accelerate AI adoption and ensure consistent agent behavior across engineering teams
Partner closely with Product Security, Cybersecurity, Architecture, and Infrastructure teams to ensure context retrieval, memory systems, knowledge access, and agent interactions meet enterprise security and compliance requirements
Drive context optimization strategies including relevance scoring, retrieval quality measurement, context window efficiency, token utilization optimization, and knowledge effectiveness across AI development workflows
Define standards and best practices for knowledge structures, metadata, content organization, context accessibility, and information quality to maximize agent performance and trustworthiness
Drive engineering excellence across the AI harness ecosystem, including observability, evaluation frameworks, performance measurement, reliability, experimentation, and continuous improvement
- Take the first step towards your dream career
- Every Dell Technologies team member brings something unique to the table. Here's what we are looking for with this role:
Essential Requirements
12+ years in software engineering, platform engineering, distributed systems, or related technical leadership roles
Strong hands-on experience with AI-assisted development, LLMs, agentic systems, RAG architectures, vector databases, knowledge systems, and enterprise AI platforms
Deep understanding of context engineering concepts including context construction, retrieval strategies, context composition, context lifecycle management, and prompt orchestration
Experience building platforms, frameworks, or services that manage knowledge retrieval, agent memory, context assembly, or AI workflow orchestration at scale
Strong understanding of AI system architecture, including embeddings, vector search, retrieval pipelines, memory architectures, agent orchestration, and tool integration patterns
Demonstrated ability to take ambiguous problems, define architectures and frameworks, and deliver practical solutions and platforms
Experience working cross-functionally with engineering, architecture, product, security, and infrastructure stakeholders
Strong written and verbal communication skills with the ability to translate complex AI concepts into actionable technical guidance
Desirable Requirements
Direct hands-on experience with agentic development platforms and tools such as GitHub Copilot, Claude Code, Cursor, Windsurf/Codeium, OpenAI, Anthropic, or equivalent technologies
Experience designing or implementing context engineering frameworks, retrieval systems, knowledge graphs, semantic search, vector databases, or memory-centric agent architectures
Familiarity with Model Context Protocol (MCP), agent toolchains, multi-agent systems, workflow orchestration frameworks, and enterprise AI governance practices
Experience optimizing context utilization, retrieval quality, token consumption, latency, and agent performance at scale
Experience building evaluation frameworks and measurement systems for context quality, retrieval effectiveness, hallucination reduction, and agent productivity
Background in developer experience, platform engineering, internal developer tooling, or enterprise AI enablement platforms
Experience operating in large enterprise environments with compliance requirements, governance controls, security review processes, and human oversight requirements
Comfort operating in ambiguity, defining new technical patterns and platform capabilities where industry standards are still evolving
Compensation
Dell is committed to fair and equitable compensation practices. The salary range for this position is $ 232,800 to $ 320,100.
Benefits and Perks of Working at Dell Technologies
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
