Senior AI Solutions Architect - OAI
Role details
Job location
Tech stack
Job description
This is a highly visible, enterprise?level architecture role focused on human?centric AI - augmenting agents, supervisors, operations teams, and executives with the right insights at the right time. We are seeking a senior architect who is technology?agnostic, capable of selecting the right tools and vendors for the job while remaining hands?on within a modern enterprise ecosystem (Azure, Databricks, Snowflake, AWS, GCP, .NET, Python). You will define enterprise patterns, guide vertical architecture teams, and translate complex AI systems into clear, compelling narratives for senior and C?suite stakeholders., Design end?to?end AI architectures connecting data, models, APIs, and user experiences across CRM, contact center, workforce management, field service, and customer operations platforms. Create shared decisioning and GenAI services (NBO/NBA, agent assistance, RAG, rules engines) so all channels reuse consistent logic and deliver trusted answers. Deliver Human?Centric AI Experiences Architect AI solutions that keep humans in the loop, with clear mechanisms for agents and supervisors to accept, adjust, or override AI recommendations. Focus on augmenting-not replacing-human decision?making. Drive High?Impact AI Capabilities Design personalization, NBO/NBA, and agent assistance solutions across voice, chat, digital, and field channels. Help architect conversational AI and agentic solutions (IVR, voicebots, chatbots, digital messaging), including knowledge search and summarization using modern frameworks where appropriate. Optimize Operations at Enterprise Scale Design AI solutions to improve sales effectiveness, customer operations efficiency, dispatch optimization, appointment scheduling, and truck?roll reduction. Drive automation of back?office workflows and use contact center analytics to continuously tune and improve AI systems. Lead Data, Governance & Reliability Define canonical data models, semantic layers, and KPIs to establish a single source of truth across analytics and AI. Ensure secure, compliant pipelines (PII, CPNI, PCI), robust monitoring for performance, drift, and cost, and enforce responsible AI practices including fairness, explainability, and reuse of shared logic. Influence Across the Enterprise Align peer architects across Care, Sales, Network, and Operations on common AI patterns and platforms. Partner with Product, PMO, and vertical delivery teams to translate architecture into epics and user stories and drive delivery through agile sprints. Executive Communication & Thought Leadership Translate complex AI architectures into simple, executive?ready visuals and narratives. Provide mentorship and thought leadership to engineers, analysts, and architects, advocating for reusable, enterprise?grade patterns.
Requirements
- 8+ years of experience in solution architecture, software engineering, or data engineering, with 4+ years delivering production AI/ML or advanced analytics.
- Strong AI/ML and GenAI proficiency, including machine learning, NLP, and conversational AI; experience with agentic frameworks preferred.
- Experience designing enterprise?scale APIs, microservices, and distributed systems in Fortune?100?scale environments.
- Proficiency with Python, .NET, Java, SQL, Scala, and modern cloud?native patterns (containers, Kubernetes, serverless, event?driven architectures).
- Technology?agnostic mindset with hands?on experience across Azure, AWS, and/or GCP, including data and AI services.
- Experience with modern data platforms (Databricks, Snowflake, Redshift) and large?scale batch and streaming pipelines.
- Strong data engineering fundamentals including data modeling, performance tuning, and governance.
- Exceptional communication skills and proven ability to influence in matrixed enterprise environments.
- Strategic mindset with the ability to define AI roadmaps and drive cross?functional execution., * Experience in telecom, cable, broadband, or high?volume contact center environments.
- Familiarity with CCaaS platforms (Genesys, Five9, Amazon Connect, NICE, Cisco, or similar).
- Master's degree in Data Science, AI/ML, or related field; PhD preferred.
- Relevant certifications (AWS or Azure Solutions Architect, TOGAF, AI/GenAI certifications).
- Six Sigma Black Belt or similar process?improvement background.
