AI Solution Architect

This role will provide central architectural support to translate business demand into production ready AI solutions, establish enterprise standards and guardrails, and reduce delivery risk across lines of business. Without this role, AI initiatives risk fragmentation, inconsistent security and governance, increased operational cost, and slower time to value. The Architect will: Responsibilities Enable faster, safer AI adoption by defining reusable architectures and engineering patterns. Ensure regulatory, security, and model risk requirements are embedded by design. Reduce duplication and rework by aligning AI investments to a single enterprise roadmap. Improve solution quality, resiliency, and cost efficiency through architectural oversight. This position is critical to scaling AI capabilities responsibly, protecting the firm, and maximizing return on investment from strategic AI platforms. Primary Skill Artificial Intelligence/Machine Learning Secondary Skill Cloud Architect Tertiary Skill Kubernetes Required Qualifications 5+ years of experience in technology architecture and solution design, including 3+ years of hands-on software engineering. 2+ years of experience designing and delivering AI/LLM solutions in enterprise environments. Hands-on experience deploying and operating solutions using Sierra AI and/or Decagon. Strong background in platform architecture, solution design, and hybrid (on-prem and cloud) deployments. Experience with AI orchestration, retrieval-augmented generation (RAG), and evaluation frameworks. Proficiency with containers, Kubernetes/OpenShift, CI/CD pipelines, and infrastructure-as-code. Strong communication skills with the ability to engage both technical and business stakeholders. Demonstrated leadership, collaboration, and mentoring capabilities. Experience with conversational AI, contact center AI, or enterprise automation. Experience designing and deploying IVR, voice-driven, or headless Agentic AI solutions, including non-UI based conversational or event-driven systems. Experience integrating AI agents with telephony, IVR platforms, or voice infrastructure including call flows, intent routing, and backend service invocation. Desired Qualifications Experience in regulated industries such as financial services. Knowledge of multiple LLM providers and model serving strategies. Familiarity with headless AI agent architectures such as background automation, system-to-system agents, and asynchronous orchestration. Understanding of voice and multi-modal AI architectures including speech-to-text, text-to-speech, intent management, and conversational state handling. Relevant cloud, security, or data certifications. Familiarity with model risk management, AI governance, and safety testing. #J-18808-Ljbffr