Agentic AI Engineer (Google ADK / GCP)
Quick Summary
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,
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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.
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Develop Core Agentic Logic: Build deterministic graph workflows that effectively weave adaptive AI reasoning with explicit execution paths to ensure predictable outcomes.
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Tool & Skill Integration: Create, map, and integrate custom Agent Skills and third-party tools (including Google Maps MCP, Search tools, and custom enterprise APIs).
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Evaluation & Debugging: Use ADK evaluation tools to test execution trajectories, manage loop limits, avoid key collisions, and drastically mitigate production hallucinations.
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Scale and Deploy: Deploy optimized agents to Agent Engine (via Cloud Run / Google Cloud Platform) and maintain high availability, security, and low latency.
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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.
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Bachelor’s degree in Computer Science, a related technical field, or equivalent practical experience.
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2+ years of experience building and deploying production-grade LLM applications or Agentic AI systems.
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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.
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Experience with the Google Cloud Platform (GCP) ecosystem, including Cloud Run, Vertex AI, Secret Manager, and Cloud Storage.
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Hands-on experience developing with the official open-source Google Agent Development Kit (ADK 2.0+).
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Deep understanding of multi-agent orchestration patterns, state graph architectures, and deterministic routing.
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Familiarity with Model Context Protocol (MCP) and integrating external tools seamlessly into LLM context windows.
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Experience implementing rigorous CI/CD pipelines for AI applications (e.g., GitHub Actions, Terraform).
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Strong background in evaluation frameworks for AI agents to benchmark precision, recall, and tool-calling accuracy.
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Location & Eligibility
Listing Details
- Posted
- July 9, 2026
- First seen
- July 9, 2026
- Last seen
- July 10, 2026
Posting Health
- Days active
- 0
- Repost count
- 0
- Trust Level
- 62%
- Scored at
- July 9, 2026
Signal breakdown
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