Jobs · Design

AI Consulting Architect

CompuNet, Inc. · Seattle, WA · 6 days ago
RemoteRemoteDesignFull-time

Why join us

CompuNet values its people more than any other asset—and realizes the contributions made by each employee are a reflection of their education, experience, certifications, expertise and passions. We strive to take care of each other, do the right thing and help our customers succeed. We work to build lasting relationships and are proud that our customers across many industries see us as a trusted advisor. Putting the customer at the center of every engagement, our mission is to design, test, deploy and support the right IT solutions for every customer.

Responsibilities

  • Act as a senior business expert and high-level technical authority in customer-facing pre-sales engagements, meeting directly with Executives, Directors, and IT leaders to understand their business challenges.
  • Translate complex enterprise business problems into compelling, tailored AI architectures and solution proposals.
  • Help organizations build and frame ROIs for AI business initiatives.
  • Lead technical discussions to highlight the value of our Enterprise AI portfolio, including:
    • Cloud: Hybrid AI workload deployment and scalability.
    • Cybersecurity: Compliance and governance frameworks, data privacy, and secure LLM integration.
    • Enterprise Networking: Edge-to-cloud connectivity, latency optimization, and infrastructure readiness for AI workloads.
    • Collaboration: Real-time AI integration, customer experience enhancements such as conversational AI, agentic AI digital workers, and omnichannel communications to improve customer experiences, productivity and operating costs.
    • Datacenter: Infrastructure design and deployment.
  • Collaborate with our engineering teams, sales teams, and technical domain leaders to define and refine the long-term strategic focus of CompuNet's AI offerings.
  • Stay ahead of emerging AI trends, industry standards, and competitive landscapes to continuously evolve our solution architecture.
  • Champion best practices for scalable, ethical, and high-performance AI deployment across our client base.

Requirements

  • 10+ years in IT architecture, enterprise engineering, and technical pre-sales, with at least 3 years specializing in Artificial Intelligence, Machine Learning, and Generative AI solutions.
  • Pre-sales acumen with a proven track record of client-facing success.
  • Demonstrable ability to lead high-stakes business discussions marrying outcome to technical solutions in front of executive leadership teams (CIOs, CTOs, CISOs, Directors).
  • Fluency in technology domains like datacenter infrastructure, cloud platforms, enterprise networking, and collaboration ecosystems.
  • AI/ML proficiency including LLMs, RAG architectures, MCP, AI model deployment, and AI governance frameworks.
  • Exceptional verbal and written communication skills with the ability to articulate deeply technical concepts to non-technical business stakeholders.
  • Experience scaling AI initiatives and driving enterprise-wide digital transformations within a consulting or systems integration environment.

Benefits

  • Medical, dental, vision, Employee Assistance Program, and Flexible Spending Accounts.
  • Life and AD&D insurance, disability coverage, critical illness, and accident insurance.
  • Employee Stock Ownership Plan (ESOP).
  • Company-matching 401(k) and profit sharing.
  • Paid Time Off (PTO) and paid holidays.

Pay

Competitive salary, with eligibility for variable compensation such as commission, bonuses, and profit sharing.

About us

CompuNet, Inc. is an engineering-led IT solution provider that offers consulting, design, and professional services. Our strength lies in our team of outcome-driven and relationship-focused professionals with a long history of designing IT solutions. Our team of highly skilled engineers take the lead in designing, developing, and implementing solutions that address complex business challenges. This team takes ownership for the entire project lifecycle, from discovery and design through deployment, training, and handoff.

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