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AI Architect
Career Insights for Natural Language Processing Engineer
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Based on Colorado data
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What they do
A Natural Language Processing Engineer specializes in developing and implementing algorithms and models tailored for understanding, processing, and generating natural language text. They utilize methodologies such as tokenization, parsing, named entity recognition, part-of-speech tagging, and other NLP techniques to perform tasks including text classification, chatbot development, and other applications where the primary input or output is natural language text.
$112,833 / year median in Colorado
Job Description
- Define and maintain TTEC's multi-model AI platform architecture across Anthropic Claude, Google Gemini / Vertex AI, and Microsoft Copilot Studio — including model selection criteria, API integration patterns, and platform governance boundaries
- Establish standards for how agents are built and composed across Google ADK and MCP — including tool design, memory and context management, orchestration patterns, and agent-to-agent communication
- Own the architectural decisions that govern how AI outputs are evaluated, monitored, and improved in production — including eval frameworks, observability instrumentation, and drift detection Cross-pillar technical coherence
- Ensure that the Automation, AI & Intelligence, and Product Engineering pillars share consistent integration patterns, data contracts, and security postures — preventing architectural drift as each pillar scales independently
- Design the interfaces between deterministic automation (RPA, Power Automate) and probabilistic AI systems (agents, bots) — defining where handoffs happen, how errors propagate, and how humans stay in the loop
- Maintain a living architecture reference — a practical, up-to-date view of how TTEC's AI systems connect, depend on each other, and evolve over time AI governance & standards
- Define and own TTEC's technical AI governance standards: prompt architecture guidelines, responsible AI design patterns, data handling requirements, and review criteria used by the
ARB/SRB/RAIC
intake process- Establish a tiered approach to AI system risk — distinguishing low-risk internal productivity tools from high-risk client-facing agentic systems — and ensure appropriate review rigor is applied to each tier
- Lead architectural reviews for new AI initiatives, serving as the technical decision-maker within the governance intake process Emerging technology leadership
- Continuously evaluate new AI frameworks, model releases, and infrastructure patterns — translating findings into concrete, time-bound recommendations for the team's roadmap
- Prototype architectural patterns before recommending them — you should be able to build a working proof of concept, not just describe one
- Contribute to TTEC's AI Agent Hub architecture: the centralized platform through which employees discover and launch AI agents across Microsoft, Google, and Anthropic tooling 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), LangGraph, 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; theARB/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 authority that makes that possible. How you'll work- You will work directly with the VP of App Delivery & Automation and the three pillar leads (Automation, AI & Intelligence, Product Engineering) as a peer technical voice — not as a consultant brought in after decisions are made.
- You will participate in the RAIC (Responsible AI Implementation Committee) and ARB (Architecture Review Board) intake processes, providing the technical architecture perspective on new AI initiatives.
- Every member of this organization uses Claude and other AI tools as a daily requirement. The AI Architect is expected to model this behavior and to actively explore how AI tooling can improve architectural practice itself.
- This role is based in the Denver metro area.