Agentic AI Engineer (Google ADK / GCP)

TTEC Digital; Bogotá; Presencial; COP 120.000.000 - 240.000.000; Jornada completa

Descripción de la vacante

TTEC Digital is seeking an Agentic AI Engineer to design, build, and scale production-ready multi-agent systems using Google’s ADK. You will bridge LLM prompting with deterministic, enterprise-grade software at scale.

You’ll deploy agents on Google Cloud Run, integrate MCP tools, and collaborate with product managers and AI researchers to advance Gemini models within agentic frameworks.

Formación

• Bachelor's degree or equivalent technical experience.
• 2+ years building production-grade LLM apps or Agentic AI systems.
• Proficiency in Python or TypeScript/Node.js.
• GCP experience: Cloud Run, Vertex AI, Secret Manager, Cloud Storage.

Responsabilidades

• Architect Multi-Agent Systems using Google ADK and MAS patterns.
• Develop core agentic logic with deterministic execution paths.
• Integrate custom Agent Skills and third-party tools (MCP, maps, APIs).
• Use ADK evaluation tools to test trajectories and reduce hallucinations.
• Deploy agents to Google Cloud Run and ensure availability and security.
• Collaborate with product managers and AI researchers to optimize Gemini models.

Conocimientos

LLM apps

Agentic AI

Deterministic workflows

CI/CD

Educación

Bachelor's degree in CS

Herramientas

GCP

Cloud Run

Vertex AI

Secret Manager

Cloud Storage

Python

TypeScript

Descripción del empleo

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.