Senior Gemini AI Engineer with GCP

Job Title :: Senior Gemini AI Engineer with GCP Location:: Dallas, TX - Hybrid Job type: Contract Duration: 6+months Open for C2C

We are seeking a highly skilled

Senior Gemini AI Engineer

to lead the design, development, and operationalization of next-generation

Agentic AI systems

. In this role, you will leverage

Google's Gemini models

and the

Google Cloud Platform (GCP)

ecosystem to build autonomous, intelligent agents capable of complex reasoning, multi-step planning, and tool execution. You will bridge the gap between cutting-edge generative AI research and enterprise-grade production software, creating multi-agent orchestration workflows that securely integrate with enterprise data streams.

Key Responsibilities Agentic System Architecture:

Design and deploy production-grade

autonomous AI agents

and multi-agent systems using the Google Agent Development Kit (ADK), Vertex AI Agent Builder , and advanced orchestration concepts (e.g., ReAct, reflection, and memory management). Gemini Implementation:

Optimize, fine-tune, and deploy

Gemini Enterprise models

vi Vertex AI , integrating advanced capabilities like tool calling, multimodal data processing, and contextual grounding. Enterprise Integration:

Build secure, real-time integrations between AI agents and enterprise platforms utilizing Model Context Protocol (MCP) toolbox, REST/SOAP APIs, and database structures like BigQuery nd Cloud Spanner. RAG Pipeline Engineering:

Develop and maintain secure Retrieval-Augmented Generation (RAG) pipelines using managed tools like Vertex AI Vector Search, AlloyDB, or BigQuery vector engines. Cloud Infrastructure & Pipelines:

Architect scalable streaming and batch pipelines on GCP using

Dataflow

, and host workloads via cloud-native runtimes like Cloud Run or Google Kubernetes Engine (GKE). AI Governance & Security:

Implement enterprise-grade security protocols, including IAM roles, VPC Service Controls, PII masking, prompt injection prevention, and Model Armor guardrails. Required Qualifications & Skills

Experience:

10+ years of professional software engineering experience, with at least 2+years of dedicated focus on

Agentic AI systems, LLM orchestration, and generative AI applications

. GCP Expertise:

Deep, hands-on experience utilizing Google Cloud Platform (GCP), specifically Vertex AI, Model Garden, and Vertex AI Pipelines. Agent Frameworks:

Proven mastery over the Google

Agent Development Kit (ADK)

and workflow tools. Familiarity with broader open-source orchestration frameworks like LangGraph, CrewAI, AutoGen, or LlamaIndex is highly valued. Core Languages:

Strong proficiency in

Python

for machine learning workflows and production API development, alongside advanced

SQL

skills for BigQuery. DevOps & LLMOps:

Experience setting up CI/CD workflows, containerized architectures (Docker, Kubernetes), and utilizing LLMOps observability tools (e.g., LangSmith, MLflow, Phoenix).