GenAI & Gemini Enterprise Engineer (Remote)

Nelnet

Scottsbluff (NE)

Hybrid

USD 130,000 - 150,000

Full time

7 days ago
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Benefits offered by this job

Medical benefits
401K
Hybrid work model

Job summary

Nelnet is seeking a GenAI Platform Engineer to own the technical build and deployment of Gemini Enterprise-based solutions for higher education and SLED clients. You will translate client needs into agentic assistants, RAG pipelines, and data integrations with a focus on quality and security.

Responsibilities include model selection, tuning, and live integrations with client systems, while collaborating with Data and Deployment teams.

Qualifications

  • Hands-on experience building GenAI/agentic AI solutions for production.
  • Experience with Gemini Enterprise Platform or Vertex AI preferred.
  • Strong knowledge of LLMs, prompting, fine-tuning, and grounding techniques.

Responsibilities

  • Design, build, and deploy agentic assistants and GenAI apps on Gemini Enterprise Agent Platform.
  • Implement RAG pipelines and grounding using platform capabilities.
  • Integrate A2A protocol and multi-agent orchestration where needed.
  • Evaluate foundation models from Model Garden based on use case, cost and performance.
  • Fine-tune or prompt-engineer models to meet accuracy, safety, and FERPA requirements.
  • Build live API and tool-calling integrations with client systems (SIS, ERP).
  • Maintain solution architecture docs and reusable connectors.
  • Deliver backlogs with technical estimates and release readiness reviews.
  • Collaborate with Data Engineers and AgentOps for data access and deployment.

Skills

GenAI solutions
Gemini Enterprise Platform
RAG pipelines
Multi-agent orchestration
Python / SDKs
Google Cloud
BigQuery / Snowflake
Model tuning / grounding
Enterprise data integration

Tools

Vertex AI
Workspace Studio
Model Garden
Gemini API
Python

Job description

Nelnet is seeking a GenAI Platform Engineer to own the technical build and deployment of Gemini Enterprise-based solutions for higher education and SLED clients. You will translate client needs into agentic assistants, RAG pipelines, and data integrations with a focus on quality and security.

Responsibilities include model selection, tuning, and live integrations with client systems, while collaborating with Data and Deployment teams.

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