AI Architect
Listed on 2026-08-27
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Software Development
Software Architect, AI Engineer (Applied/Software)
AI Architect
TTEC's App Delivery & Automation organization is in the midst of a meaningful transformation — moving from a traditional engineering model organized around technology stacks to an AI-first delivery engine organized around outcomes. Three distinct pillars now power this organization:
Automation (RPA, shop floor), AI & Intelligence (bots, agentic AI, GenAI), and Product Engineering (SaaS products, desktop and business applications). The AI Architect is a new role created to give this transformation a coherent technical spine. You will own the architecture layer that sits across all three pillars — defining how AI systems are designed, how platforms are selected and integrated, how data flows between systems, and how decisions made in one pillar stay consistent with decisions made in another.
This is not a strategy role that produces documents. It is a hands-on technical leadership role. You will design systems, review implementations, prototype new patterns, and be the person others come to when a hard architectural question needs a definitive answer. You report directly to the VP of App Delivery & Automation and carry director-level authority to set and enforce architectural standards across the organization.
You must be located in Denver, Colorado.
What you'll own:
- AI platform architecture
- Cross-pillar technical coherence
- AI governance & standards
- Emerging technology leadership
What you'll bring to the role:
- 12+ years of software and systems architecture experience, with at least 4 years focused on AI/ML systems, LLM application architecture, or intelligent automation at enterprise scale
- Deep, hands-on experience with large language model APIs and agent frameworks — you have built production agentic systems, not just evaluated them
- Demonstrated ability to architect across multiple AI platforms simultaneously (e.g., Anthropic + Google + Microsoft) and make principled decisions about where each platform fits
- Strong working knowledge of Model Context Protocol (MCP) — including designing MCP servers, exposing enterprise systems as tools, and integrating MCP into agent orchestration layers
- Experience designing AI governance frameworks: risk tiering, review processes, responsible AI standards, and human-in-the-loop patterns for enterprise deployments
- Ability to operate at multiple levels of abstraction — from whiteboard architecture to working prototype — without losing sight of either
- Strong communication skills with both technical and non-technical audiences; comfortable presenting architectural recommendations to senior leadership
Preferred experience:
- Hands-on experience with Google Agent Development Kit (ADK), Lang Graph, or comparable orchestration frameworks for multi-agent systems
- Experience architecting AI systems in BPO, contact center, or enterprise SaaS environments — understanding the operational constraints of high-volume, low-latency, compliance-sensitive deployments
- Familiarity with RPA platforms (Power Automate, UiPath) and experience defining the architectural boundary between RPA and agentic AI
- Experience with Azure AI services, Google Vertex AI, and the integration patterns that connect these platforms to enterprise data and identity systems
- Exposure to shop floor or operational technology (OT) environments — understanding the unique constraints of AI systems that interact with physical operations
- Prior experience in a formal architecture governance role (enterprise architect, principal architect, or equivalent)
How success is measured:
- In the first 90 days, success looks like: a clear, documented view of TTEC's current AI architecture across all three pillars; identified gaps and inconsistencies; and a prioritized set of architectural decisions to resolve.
- By six months: architectural standards are in place and being applied to new initiatives; the ARB/RAIC review process has a clear technical architecture gate; and at least one cross-pillar integration pattern has been designed, prototyped, and adopted.
- By one year: the organization is building AI systems that are architecturally consistent, independently scalable, and governable — and the AI Architect is the recognized technical…
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