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Dell Technologies·Other·2 days ago
2 days ago

Agentic Context Engineering Architect & AI Practitioner

Hopkinton, United States of AmericaFull-timeOn-siteSenior · 12+ yearsArchitect

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Must-have skills for this role

  • llms
  • agentic systems
  • rag architectures
  • vector databases

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What you'll do

  • 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

What they're looking for

  • 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

Nice to have

  • 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

Summarised by NextRaise from the employer’s description, which follows in full below.

Full description from employer

SUMMARY

Agentic Context Engineering Architect & AI Practitioner 

Join us to do the best work of your career and make a profound social impact as an Agentic Context Engineering Architect & AI Practitioner on our AI Development & Agent Ops team in Hopkinton, MA.

About Dell Technologies — ISG Developer Experience

Dell's Infrastructure Solutions Group is a global leader in Solutions, Storage, Compute, and Networking. The Developer Experience organization within ISG is responsible for developer productivity, tooling, observability, and platform engineering for approximately 9,000 engineers. Our current mandate spans agentic SDLC transformation, AI tooling governance, and the operating model changes required to make AI-assisted development the norm — not the exception. 

Infrastructure Solutions Group (ISG) builds the products that power infrastructure, solutions, and data management our customers need most. Our teams design and develop the hardware and software that connect infrastructure, accelerate computational workloads, integrate across the stack, protect data continuity, and deliver the platforms, applications, and diagnostics our customers rely on every day at enterprise scale. 

Some product builders follow the rules. Ours rewrite them.

Within ISG, innovation isn't just about creating new technology- it's about challenging assumptions and reimagining how work gets done. Engineers define intent, author precise specifications, and orchestrate AI agents that execute at speed and scale. AI is embedded throughout our development process, helping us move faster, learn quicker, and deliver greater impact. Yet the most important contribution remains uniquely human: deciding what to build, designing how it should work, and applying the judgment needed to earn our customers' trust. When your products power critical infrastructure around the world, that responsibility matters.

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

Other

Company

Dell TechnologiesOther
Hopkinton, United States of America

Company facts come from this company's own listings. We only show what the postings themselves carry.

Sourced from Dell Technologies's careers site·first seen 18 Sept 2026·last verified 18 Sept 2026·How we source jobs

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