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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in enterprise AI architecture, including generative AI and MLOps, while providing leadership in technical governance and solution validation. Capable of developing AI Factory standards and mentoring engineering teams to ensure delivery quality and scalability.
Highest-signal resume keywords
Enterprise AI ArchitectureGenerative AI SolutionsMLOps ImplementationNVIDIA AI TechnologiesTechnical Governance
Tech Stack
Tools & technologiesAbout the role
Key responsibilities & impact- Define project strategies and technical options balancing customer goals, architectural requirements, delivery risk, operational readiness, and financial constraints
- Provide leadership and expert advice on enterprise AI architecture, generative AI, agentic systems, MLOps, model serving, integration, governance, and accelerated infrastructure
- Interface with client technical and business executives, project leadership, partners, and internal stakeholders
- Lead architecture reviews, technical governance, escalation management, solution validation, and quality oversight for complex AI engagements
- Support strategic sales pursuits through discovery, solution shaping, proposals, SOWs, ROMs, LOEs, presentations, and executive workshops
- Develop standards, best practices, training, and technical guidance for AI software implementations
- Define and maintain AI Factory software engineering standards, delivery methodologies, architecture patterns, and quality practices
- Develop repeatable AI Factory service offerings, accelerators, deployment frameworks, and reference architectures
- Evaluate emerging AI technologies, tools, and partner ecosystems to guide technical direction and investment priorities
- Drive delivery consistency, quality, and scalability across AI software engineering engagements
- Mentor consulting engineers, senior engineers, architects, and technical leads
- Partner with sales, architecture, delivery, and practice leadership on service strategy and go-to-market offerings
- Represent CDW as a technical thought leader with strategic clients, partners, and industry communities
Requirements
What you’ll need- Bachelor’s degree and 6 years of hands-on software, data, infrastructure, or AI solution experience, including three years of consulting experience with large enterprises and cross-functional projects OR 10 years of hands-on software, data, infrastructure, or AI solution experience, including three years of consulting experience with large enterprises and cross-functional projects
- Experience architecting enterprise generative AI, agentic AI, RAG, model-serving, MLOps, fine-tuning, or distributed inference solutions
- Advanced knowledge of NVIDIA NIM, NVIDIA Blueprints, NVIDIA AI Enterprise, Python, APIs, containers, Kubernetes, CI/CD, AI observability, evaluation, security, and production operations
- Understanding of GPU infrastructure and hardware-software tradeoffs affecting AI performance, scalability, reliability, and cost
- Ability to research complex technology solutions, evaluate alternatives, make recommendations, and present materials for enterprise clients
- Excellent written, presentation, and verbal communication skills, including presenting technology recommendations from a business perspective
- Ability to work calmly and productively amid change, ambiguity, and risk
- Ability and willingness to work beyond regularly scheduled shifts, select weekends, or overtime as necessary
- Ability and willingness to travel as needed to CDW locations or client sites
- Valid U.S. driver’s license
- Experience shaping enterprise AI strategy, operating models, governance, application modernization, or large-scale AI transformation programs, a plus
- Experience guiding partner alignment and technical strategy across NVIDIA, Microsoft, data, security, and software ecosystems, a plus
- Experience developing consulting offerings, intellectual property, architecture standards, technical enablement, or reusable delivery assets, a plus
- Preferred NVIDIA certifications aligned to the role include NVIDIA-Certified Professional Generative AI LLMs (NCP-GENL) and NVIDIA-Certified Professional Agentic AI (NCP-AAI), a plus
Benefits
Comp & perks- Annual bonus target of 10% subject to terms and conditions of plan
- Benefits overview available at https://cdw.benefit-info.com/
- Collaborative environment
- Supported professional growth
- Equal opportunity employment
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
AI Solution ExperienceModel ServingFine-TuningDistributed InferencePython ProgrammingAPIs DevelopmentKubernetes ManagementCI/CD PracticesAI ObservabilityGPU Infrastructure Understanding
Soft Skills
Excellent Communication SkillsAbility to Work Amid ChangePresentation SkillsMentoring AbilityProblem-Solving Skills
Tools & Technologies
NVIDIA NIMNVIDIA BlueprintsNVIDIA AI EnterpriseContainersAI Governance ToolsDeployment FrameworksReference Architectures
Certifications & Qualifications
NVIDIA-Certified Professional Generative AI LLMs (NCP-GENL)NVIDIA-Certified Professional Agentic AI (NCP-AAI)
Industry Keywords
AI StrategyCross-Functional ProjectsConsulting ExperienceEnterprise ClientsTechnical Enablement