AI Solutions Architect opening in Denver, CO (Onsite)

About the role

We are looking for a AI Solutions Architect to sit at the intersection of advanced AI and the real world of telecom and contact centers supporting Sales, Customer Operations, Marketing, and Field Services.

Your goal: ensure agents, customers, and executives always get the same, trusted answer, no matter where or what they ask from our AI and analytics stack.

We are focused on humancentric AI that augments humans, not replaces them—supporting agents, supervisors, and operations teams with the right insight at the right moment.

Responsibilities

• Own the AI Blueprint
• Design end-to-end architectures that connect data, models, APIs, and UIs across CRM, contact center, and customer operations platforms (WFM, field service, ticketing).
• Design shared decisioning and GenAI services (NBO/NBA, agent assistance, RAG, rules engines) so all channels reuse the same logic and deliver consistent offers, actions, and responses.
• Ensure architectures are humancentric, keeping humans in the loop with clear controls to accept, adjust, or override AI suggestions.
• Deliver High-Impact AI Experiences
• Architect NBO/NBA and personalization solutions for sales, retention, and service across voice, chat, digital, and field channels in partnership with stakeholders and vertical development teams.
• Help design agent assistance experiences (e.g., recommended actions, offers, and realtime coaching) that help agents and supervisors make better decisions.
• Help design conversational AI and agentic solutions for IVR, voicebots, chatbots, and digital messaging, as well as knowledge search and summarization, leveraging frameworks such as LangChain / LangGraph where applicable.
• Optimize Operations at Scale
• Design AI solutions for sales effectiveness, customer operations efficiency and customer experience, dispatch optimization, appointment scheduling, and truckroll reduction.
• Drive automation of backoffice flows (order fallout, provisioning exceptions, billing investigations, service assurance).
• Use contact center data and analytics (interaction data, routing, handle time, outcomes) to continuously tune and improve AI and automation solutions.
• Lead Data, Governance & Reliability
• Define canonical data models, semantic layers, and KPIs so analytics and AI all use a single source of truth.
• Ensure secure, compliant data pipelines (PII, CPNI, PCI) and robust monitoring for performance, drift, and cost.
• Implement responsible AI practices (safety, fairness, explainability) and enforce reuse of shared models, rules, and prompts so products do not diverge in answers or behaviors.
• Influence Across the Enterprise
• Align peer Solutions Architects on common AI patterns and platforms across Care, Sales, Network, and Operations.
• Partner with PMO, Product, and vertical development teams to turn architectures into epics and user stories, sequence work, and drive delivery through agile sprints (planning, refinement, reviews, demos).
• Translate complex AI concepts into simple, business-focused narratives for senior and executive stakeholders, including those without technical backgrounds, enabling clear decisions.
• Provide thought leadership and mentoring to engineers, analysts, and architects; advocate for consistent, reusable patterns across teams.

Requirements

• Experience
• 8+ years in solution architecture, software engineering, or data engineering, with 4+ years delivering production AI/ML or advanced analytics.
• Background in telecom, cable, broadband, or other high-volume customer service environments is a strong plus.
• Experience with contact center data & analytics (voice, chat, IVR, routing, quality/performance metrics) is preferred.
• Familiarity with CCaaS applications and architectures (e.g., Genesys, Five9, Amazon Connect, NICE, Cisco, or similar) is a plus.
• AI & Engineering Skills
• Strong ML/AI proficiency (machine learning, deep learning, NLP, GenAI); hand-on experience with agentic frameworks is preferred.
• Proficiency in major languages (Python, .NET, Java, SQL, Scala) and modern APIs/microservices for Fortune 100-scale enterprise systems.
• Experience with containers and cloud-native patterns (Docker, Kubernetes, serverless, event-driven architectures).
• Experience designing conversational AI solutions
• Cloud, Data & Platform
• Technology-agnostic mindset with hands-on experience across major clouds; ability to choose the right platform or technology for the problem, including vendor selection.
• Practical experience with one or more of: Azure, AWS, Google Cloud Platform, especially their data & AI services.
• Familiarity with modern data platforms such as Databricks, Snowflake, Redshift, and building pipelines (batch/streaming) using Kafka/Event Hubs or similar.
• Solid data engineering fundamentals: data modeling, performance tuning, and governance.
• Leadership & Communication
• Proven ability to influence horizontally in a matrixed environment and align multiple vertical architecture teams.
• Exceptional communication skills: you reduce complex architectures into clear, concise visuals and narratives for senior executives and nontechnical stakeholders.
• Strategic mindset with the ability to define AI roadmaps and drive cross-functional execution.