AI Architect

Job Description

We are seeking an experienced Application Architect III to provide central architecture leadership for enterprise AI adoption. The architect shall translate business demand into production-ready AI solutions, establish enterprise standards and guardrails, and reduce delivery risk across lines of business. This role is critical to scaling AI capabilities responsibly, embedding regulatory and security controls by design, and maximizing return on investment from strategic AI platforms.

Responsibilities:

• Define reusable AI architectures and engineering patterns to enable faster, safer adoption.
• Embed regulatory, security, and model risk requirements by design across solutions.
• Align AI investments to a single enterprise roadmap to reduce duplication and rework.
• Provide architectural oversight to improve quality, resiliency, and cost efficiency.
• Design and guide delivery of AI/LLM solutions, including orchestration, RAG, and evaluation frameworks.
• Partner with business and engineering stakeholders to shape end-to-end solution designs.
• Mentor teams on platform architecture, hybrid deployments, and DevSecOps practices.
• Validate digital and voice architectures for conversational, IVR, and agentic AI use cases.

Required Skills & Qualifications:

• 5 years in technology architecture and solution design, including 3 years of hands-on software engineering.
• 2 years 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 to engage 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 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.

Preferred Skills:

• Experience in regulated industries such as financial services.
• Knowledge of multiple LLM providers and model serving strategies.
• Familiarity with headless AI agent architectures, including 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.