Agentic AI Engineer – Google ADKGCP
Austin, TX - USA
Job Summary
As an Agentic AI Engineer specializing in Googles 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 will 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.
What skills and experience you will bring:
- Bachelors degree in computer science Software Engineering Artificial Intelligence Machine Learning or a related technical discipline; equivalent practical experience will also be considered.
- 2 years of hands-on experience designing developing and deploying production-grade Generative AI Large Language Model (LLM) or Agentic AI applications in enterprise environments.
- Strong software engineering proficiency in Python and/or TypeScript/ including modern development practices dependency management testing frameworks API development and CI/CD pipelines.
- Experience building autonomous AI agents intelligent workflows retrieval-augmented generation (RAG) solutions or multi-step LLM applications that interact with external systems and data sources.
- Hands-on experience with Google Cloud Platform (GCP) including services such as Vertex AI Cloud Run Cloud Storage Secret Manager IAM and cloud-native application deployment patterns.
- Solid understanding of prompt engineering tool calling function execution agent memory management context optimization and LLM application architecture.
- Experience integrating AI solutions with enterprise APIs databases knowledge repositories and third-party platforms while maintaining security scalability and observability standards.
- Strong troubleshooting and debugging skills with the ability to monitor optimize and improve AI application performance in production environments.
Preferred qualifications:
- 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.
Required Experience:
Unclear Seniority
About Company
We believe that humanity and technology should âco-exist, and that at the nexus of the âmost powerful experiences, humanity and technology collide. At TTEC Digital, we combine the expertise, innovation, partnerships, and passion of three industry-leading customer experience com ... View more