Applied AI Architect, Large Enterprise

Responsibilities

• Serve as the primary technical advisor and long-term technical relationship owner for a portfolio of existing enterprise customers and pre-sales prospects.
• Partner with Account Directors on account strategy while owning technical account plans, milestones, adoption priorities, and expansion opportunities.
• Lead executive and technical discovery to identify, qualify, and prioritize AI use cases tied to business outcomes.
• Develop applied AI architectures spanning models, applications, data, integration, security, privacy, governance, evaluation, and deployment.
• Guide technical evaluations, demonstrations, workshops, prototypes, and proofs of value through production adoption.
• Maintain use-case portfolios with decision criteria, ownership, blockers, success measures, delivery needs, and adoption plans.
• Build relationships with CTOs, CIOs, CISOs, AI leaders, engineering teams, and other stakeholders.
• Coordinate Deployment Engineering, implementation, training, enablement, product, domain specialists, partners, and delivery teams.
• Track adoption, usage, account health, production readiness, and measurable customer impact; intervene when risks threaten value realization.
• Share customer insights with Product, Engineering, and Research to improve products and reusable architecture guidance.

Requirements

• Significant experience in customer-facing technical roles such as solutions architecture, solutions engineering, technical account leadership, AI deployment, or technical customer success.
• Experience guiding enterprise organizations from technical evaluation through production adoption and measurable business impact.
• Strong software and cloud architecture foundations, including APIs, distributed systems, data integration, identity, security, and privacy.
• Understanding of modern AI systems, large language models, agentic applications, model evaluation, retrieval, or enterprise AI workflows.
• Ability to prototype and work with APIs, SDKs, and programming languages such as Python or JavaScript.
• Experience developing technical account plans, prioritizing complex customer portfolios, and connecting adoption to measurable outcomes.
• Relevant industry expertise or strong fluency with digital-native business needs.
• Clear communication skills and the ability to turn ambiguity into practical technical narratives, executive decisions, or action plans.
• Ability to collaborate across disciplines and support responsible AI deployment.