About the Role TTEC is scaling its Automation & AI portfolio to move beyond manual, ticket-by-ticket process work toward an agentic framework that can right-source work across business units. This role is central to that shift — building the multi-agent systems, integrations, and evaluation rigor needed to deploy AI agents safely and at scale across TTEC's technology and business operations. What You'll Do • Design and implement multi-agent workflows using Google Agent Development Kit (ADK), including agent orchestration, tool routing, and memory/context management • Build integrations using Model Context Protocol (MCP) to expose internal systems (Jira, SharePoint, ServiceNow, internal APIs, etc.) as discoverable tools that agents can call at runtime • Develop and maintain evaluation frameworks to measure agent accuracy, task completion rate, and safety — both pre- and post-deployment • Design, build, and optimize conversational and task-based agents in Microsoft Copilot Studio, integrating with Power Platform (Power Automate, Dataverse) and enterprise data sources • Apply strong prompt engineering practices — structured prompting, few-shot design, guardrails, and iterative evaluation — to improve agent reliability and reduce hallucination/drift • Architect and deploy agentic solutions on Google Cloud Platform (GCP) (Vertex AI, Cloud Functions, Cloud Run, IAM) with attention to scalability, cost, and security • Partner with business unit stakeholders to identify manual, repeatable processes suitable for agent-based automation, translating business requirements into technical agent designs • Collaborate with the Automation & AI team on reusable patterns, shared tooling, and governance standards (security review readiness, access control, data handling) • Contribute to internal enablement — documentation, training, and knowledge transfer so the broader team can build and extend agentic solutions • Monitor deployed agents in production, iterating based on performance data, user feedback, and evaluation results What You'll Bring Required: • Hands-on experience building with Google Agent Development Kit (ADK) or comparable agent orchestration frameworks (LangGraph, AutoGen, CrewAI) • Practical experience with Model Context Protocol (MCP) — building or consuming MCP servers/tools • Strong prompt engineering skills, including evaluation-driven prompt iteration • Experience with Microsoft Copilot Studio for building and deploying enterprise agents/bots • Working knowledge of GCP services relevant to AI workloads (Vertex AI, Cloud Functions/Run, IAM, logging/monitoring) • Solid software engineering fundamentals — Python (preferred), API design, version control • Understanding of LLM evaluation methodology: accuracy, task completion, safety/guardrail testing