Remote GenAI & Gemini Enterprise Engineer on Google Cloud

Nelnet; Columbus (NE); Hybrid; USD 130,000 - 150,000; Full time

Benefits offered by this job

Medical, dental, vision

HSA and FSA

401K/student loan repayment

Life insurance & AD&D

Wellness program

Generous earned time off

Job summary

Nelnet is seeking a GenAI Platform Engineer to lead the build and deployment of agentic AI solutions on the Gemini Enterprise Platform. You will translate client requirements into scalable, production-ready capabilities, including RAG pipelines, model integration, and multi-agent orchestration.

You will collaborate with Data and AgentOps teams to ensure data readiness, deployment quality, and secure, compliant implementations across higher education and SLED clients.

Qualifications

• Hands-on experience building GenAI/agentic AI solutions in production.
• Experience with Gemini Enterprise Platform or Vertex AI preferred.
• Knowledge of LLM prompts, tuning, grounding, and RAG pipelines.
• Familiarity with cloud data, compute, and access-control services (IAM, BigQuery).
• Ability to translate backlog items into working technical solutions.

Responsibilities

• Design, build, and deploy agentic assistants and GenAI apps on Gemini Enterprise Platform.
• Implement RAG pipelines and grounding using search capabilities.
• Integrate A2A protocols and multi-agent orchestration where needed.
• Build live API integrations with client systems (SIS, ERP).
• Maintain solution architecture docs and reusable playbooks.

Skills

GenAI solutions

RAG pipelines

Multi-agent orchestration

Python

Google Cloud

Gemini Enterprise

Model tuning

LLM deployment

APIs

Evaluation harnesses

Education

Bachelor's or higher in CS/related field

Tools

Gemini Enterprise Platform

Vertex AI

Model Garden

BigQuery

Snowflake

Cloud Run/GKE

IAM

Git

Job description

Nelnet is seeking a GenAI Platform Engineer to lead the build and deployment of agentic AI solutions on the Gemini Enterprise Platform. You will translate client requirements into scalable, production-ready capabilities, including RAG pipelines, model integration, and multi-agent orchestration.

You will collaborate with Data and AgentOps teams to ensure data readiness, deployment quality, and secure, compliant implementations across higher education and SLED clients.