AI Solutions Architect

The team is looking for an AI Coach. Someone that the team (PhD and DS staff) can come to for guidance on which model(s) should be used to start building a solution based on the business use case. They are looking for someone that is so experienced (20-30 models they have built), that they can recommend which models to use for the use case, because they have enough experience to say things like “GPT 3.0 and the Claud Model is better for this use case because of XYZ”. The reason the client is looking for this role is to expedite the development process. Instead of trying to build something 4 times using 4 different models (trial by error), they are looking for a resource that can help the team shorten the development life cycle by starting them off in a better direction from the onset (build it 1-2 times vs. 4-5) to get to the end solution., * 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 human centric, 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 real time 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 truck roll reduction.
• Drive automation of back office 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., Key Responsibilities Solution Leadership & Strategy Lead solution design and strategy for large, complex government pursuits Define and oversee technical win themes, discr…
• 1 day ago +

• Strong expertise in AI/ML, including deep learning, NLP, LLMs, and RAG - No less than 4 years
• Proven experience architecting and delivering end-to-end AI solutions in cloud environments Azure, AWS, GCP
• Able to define the right technical direction, architecture, and solution approach for enterprise AI initiatives
• Strong understanding of scalable AI design, integration, deployment, and operationalization
• Excellent communication skills with the ability to guide both technical teams and business stakeholders
• Ideal profile is a strategic technical leader who can steer the team toward the right long-term AI/ML direction, * 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); hands on experience with agentic frameworks (e.g., LangChain, LangGraph or similar) 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 (IVR, voicebots, chatbots, digital assistants) is a plus.

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, GCP, 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 non technical stakeholders.
• Strategic mindset with the ability to define AI roadmaps and drive cross functional execution.

Preferred Certifications

• AWS Certified Solutions Architect
• Microsoft Azure Solutions Architect Expert
• TOGAF
• AI/GenAI certifications (e.g., Agentic AI Business Solutions Architect, Azure AI Engineer)