Generative AI Deployment Engineer – Onsite

Tiger Analytics; United States; Hybrid; USD 120,000 - 210,000; Full time

Job summary

Tiger Analytics is seeking an experienced Forward Deployed Engineer (Generative AI) to join our analytics consulting practice and lead on-site deployment, integration, and scaling of enterprise Gen AI solutions. You will embed with customer engineering teams to operationalize LLMs and retrieval systems on Google Cloud Platform (GCP).

Work closely with AI researchers, data scientists, and platform engineers to design scalable architectures, implement end-to-end data and retrieval pipelines, and

Qualifications

• Experience deploying Gen AI solutions on enterprise-scale environments.
• Strong knowledge of GCP Vertex AI and related tooling.
• Proficiency with Python and cloud-native ML Ops workflows.
• Hands-on experience with LLM orchestration and vector databases.
• Ability to travel to client sites for on-site deployments.

Responsibilities

• Deploy, fine-tune, and scale Gen AI models in customer environments.
• Architect scalable AI infrastructure for GPU/TPU workloads.
• Design high-throughput data and retrieval pipelines for RAG.
• Advise on AI safety, prompt engineering, and cost optimization.
• Collaborate with AI researchers and platform teams to improve products.

Skills

Python

GCP

Vertex AI

LLM orchestration

Kubernetes

Tools

Vertex AI Studio

Model Registry

Endpoint deployment

Vertex AI Pipelines

Vertex AI Vector Search

LangChain

LlamaIndex

AutoGen

PyTorch

Hugging Face

Milvus

Pinecone

pgvector

vLLM

TGI

Triton Inference Server

GKE

Terraform

Google Cloud SDK

Job description

Tiger Analytics is seeking an experienced Forward Deployed Engineer (Generative AI) to join our analytics consulting practice and lead on-site deployment, integration, and scaling of enterprise Gen AI solutions. You will embed with customer engineering teams to operationalize LLMs and retrieval systems on Google Cloud Platform (GCP).

Work closely with AI researchers, data scientists, and platform engineers to design scalable architectures, implement end-to-end data and retrieval pipelines, and