Gen AI Deployment Engineer – Scale LLMs Across Clouds

Tiger Analytics

New York (NY)

On-site

USD 140,000 - 190,000

Full time

14 days+
Application generator

An application made for this job — a tailored resume and cover letter that speak straight to the posting.

Get past ATS filters

Benefits offered by this job

Career development
Equal employment opportunity

Job summary

Tiger Analytics is seeking an experienced Forward Deployment Engineer (Generative AI) to drive on-site deployment, integration, and scaling of enterprise Gen AI solutions. You will embed within customer engineering teams to operationalize LLMs across multi-cloud environments (AWS, Azure, GCP) and bridge research with production-grade infrastructure.

You will collaborate with cross-functional teams and business partners to ensure business value and communicate results, shaping current and future

Qualifications

  • Proven experience with Model Garden and Vertex AI Pipelines.
  • Advanced knowledge of SQL for BigQuery and Python for ML engineering.
  • Hands-on experience with Google Cloud Storage and Vertex AI endpoints.
  • Familiarity with stateful real-time processing and agentic architectures.

Responsibilities

  • Deploy, integrate, and scale enterprise Generative AI solutions on-site.
  • Embed within customer engineering teams to operationalize LLMs and retrieval systems across multi-cloud environments.
  • Collaborate with cross-functional teams to translate business goals into robust technical architectures.
  • Provide regular, structured status updates and drive strategy with data-driven insights.

Skills

Vertex AI Mastery
BigQuery SQL
Python for ML
Agentic architectures

Tools

ADK
Vertex AI Agent Builder
MCP Toolbox
BigQuery & Spanner integration

Job description

Tiger Analytics is seeking an experienced Forward Deployment Engineer (Generative AI) to drive on-site deployment, integration, and scaling of enterprise Gen AI solutions. You will embed within customer engineering teams to operationalize LLMs across multi-cloud environments (AWS, Azure, GCP) and bridge research with production-grade infrastructure.

You will collaborate with cross-functional teams and business partners to ensure business value and communicate results, shaping current and future

Get your free, confidential resume review.

or drag and drop your file here.

Similar jobs

Similar jobs worth comparing

Gen AI Deployment Engineer — On-Site
Gen AI Deployment Engineer — On-Site

Tiger Analytics Inc. • United States

Remote
USD 140,000 - 200,000
Generative AI Forward-Deployed Engineer (On-Site)
Generative AI Forward-Deployed Engineer (On-Site)

Tiger Analytics, LLC • New York (NY)

On-site
USD 150,000 - 210,000
Generative AI Forward Deployed Engineer (On‑Site)
Generative AI Forward Deployed Engineer (On‑Site)

Tiger Analytics • Austin (TX)

On-site
USD 140,000 - 210,000
Gen AI Forward Deployed Engineer - Onsite Deployment
Gen AI Forward Deployed Engineer - Onsite Deployment

Tiger Analytics • United States

On-site
USD 120,000 - 160,000
Generative AI Forward-Deployed Engineer - Onsite AI
Generative AI Forward-Deployed Engineer - Onsite AI

Tiger Analytics • Chicago (IL)

On-site
USD 140,000 - 190,000
Azure AI & UiPath Engineer – Deploy & Scale GenAI
Azure AI & UiPath Engineer – Deploy & Scale GenAI

Tiger Analytics Inc. • United States

On-site
USD 150,000 - 230,000
Gen AI Forward-Deployed Engineer - On-Site AI Deployment
Gen AI Forward-Deployed Engineer - On-Site AI Deployment

Tiger Analytics, LLC • United States

On-site
USD 120,000 - 160,000
Forward-Deployed GenAI Engineer: Production LLMs & Agents
Forward-Deployed GenAI Engineer: Production LLMs & Agents

Tiger Analytics Inc. • Dallas (TX)

On-site
USD 140,000 - 190,000
Forward Deployed Engineer, Generative AI (Enterprise)
Forward Deployed Engineer, Generative AI (Enterprise)

Tiger Analytics • Dallas (TX)

On-site
USD 150,000 - 190,000
Generative AI Forward-Deployed Engineer (GCP/LLM Ops)
Generative AI Forward-Deployed Engineer (GCP/LLM Ops)

Tiger Analytics • Mountain View (CA)

On-site
USD 140,000 - 200,000