Agentic AI Engineer (Google ADK / GCP)

At TTEC Digital, we coach clients to ensure their employees feel valued, and fully supported, because an amazing customer experience is an employee first process. Our vision is the same, a place where employees know they can thrive. As an Agentic AI Engineer specializing in Google’s Agent Development Kit (ADK), you will design, build, and scale production-ready Multi-Agent Systems (MAS) and complex AI workflows. You will bridge the gap between simple LLM prompting and robust, deterministic, enterprise-scale software engineering. In this role, you will leverage ADK to orchestrate specialized micro-agents, build reliable graph-based workflows, and integrate AI agents seamlessly with enterprise datastores, APIs, and Model Context Protocol (MCP) tools. You will be responsible for moving AI from conceptual prototypes to high-throughput, mission-critical business systems deployed on Agent Engine. What You'll Be Doing Architect Multi-Agent Systems: Design and implement structured multi-agent architectures (Sequential Pipelines, Parallel Fan-out/Gather, and Loop-based self-correction) using Google ADK. Develop Core Agentic Logic: Build deterministic graph workflows that effectively weave adaptive AI reasoning with explicit execution paths to ensure predictable outcomes. Tool & Skill Integration: Create, map, and integrate custom Agent Skills and third-party tools (including Google Maps MCP, Search tools, and custom enterprise APIs). Evaluation & Debugging: Use ADK evaluation tools to test execution trajectories, manage loop limits, avoid key collisions, and drastically mitigate production hallucinations. Scale and Deploy: Deploy optimized agents to Agent Engine (via Cloud Run / Google Cloud Platform) and maintain high availability, security, and low latency. Collaborate across Ecosystems: Work alongside product managers and core AI researchers to optimize the implementation of Gemini models ($Gemini\ 2.5\ Flash$, Pro, etc.) within agentic frameworks. What You'll Bring to the Role Bachelor’s degree in Computer Science, a related technical field, or equivalent practical experience. 2+ years of experience building and deploying production-grade LLM applications or Agentic AI systems. Strong proficiency in at least one primary language supported by ADK: Python (e.g., managing virtual environments using uv or pip) or TypeScript/Node.js. Experience with the Google Cloud Platform (GCP) ecosystem, including Cloud Run, Vertex AI, Secret Manager, and Cloud Storage. What Will Help You Succeed Hands-on experience developing with the official open-source Google Agent Development Kit (ADK 2.0+). Deep understanding of multi-agent orchestration patterns, state graph architectures, and deterministic routing. Familiarity with Model Context Protocol (MCP) and integrating external tools seamlessly into LLM context windows. Experience implementing rigorous CI/CD pipelines for AI applications (e.g., GitHub Actions, Terraform). Strong background in evaluation frameworks for AI agents to benchmark precision, recall, and tool-calling accuracy. #LI-BN1