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Forward Deployment Engineer - Gen AI

2 weeks, 4 days ago
United States, Canada
Full-time
Senior
AI Engineer
DevOps and Infrastructure
AWS Azure GCP Generative AI Go Hugging Face Kubernetes LLM Machine Learning Python PyTorch SageMaker Terraform Vertex AI
Apply Now
Tiger Analytics

Tiger Analytics

Tiger Analytics is a leading advanced analytics consulting firm partnering with Fortune 100 companies to drive business value through expertise in marketing science, customer analytics, and operations analytics.

Professional Services
1K-5K
Founded 2011
View All Jobs 26

Description

  • Deploy, fine-tune, and optimize large-scale Generative AI models and LLM orchestration frameworks in customer cloud environments.
  • Architect scalable infrastructure for AI workloads using GPU/TPU orchestration, high-performance storage, and low-latency networking.
  • Design and implement high-throughput data ingestion pipelines and vector database architectures for Retrieval-Augmented Generation (RAG).
  • Build resilient, cloud-agnostic deployments across AWS, Azure, and GCP using Infrastructure as Code.
  • Serve as the primary technical consultant for enterprise clients on AI safety, prompt engineering patterns, and inference cost optimization.
  • Embed with customer engineering teams to drive on-site deployment, integration, and scaling efforts.
  • Collaborate with research and platform engineering teams by sharing deployment insights and edge cases to improve product robustness.
  • Troubleshoot issues across the full stack, from GPU drivers and infrastructure layers to prompt engineering logic.
  • Travel to client sites and lead high-stakes deployment sprints as needed.

Requirements

  • Hands-on experience with LLM orchestration tools such as LangChain, LlamaIndex, or AutoGen.
  • Experience with deep learning frameworks such as PyTorch and Hugging Face.
  • Production experience with vector databases such as Milvus, Pinecone, Qdrant, Chroma, or pgvector.
  • Proficiency with model serving frameworks such as vLLM, TGI, or Triton Inference Server, plus evaluation tools.
  • Advanced knowledge of AWS Bedrock/SageMaker, Azure OpenAI, or GCP Vertex AI.
  • Strong experience with Kubernetes for GPU workloads.
  • Mastery of Terraform or OpenTofu for provisioning complex multi-cloud compute environments.
  • Strong coding skills in Python, preferred, or Go, with an emphasis on clean, concurrent code.
  • Ability to manage customer expectations around LLM non-determinism, hallucinations, and performance trade-offs.
  • Willingness to travel to client sites for on-site deployment work.
  • Passion for keeping pace with rapid advancements in Generative AI.
  • Exceptional debugging ability across multiple software layers.
  • Experience in a fast-growing consulting or entrepreneurial environment is beneficial.

Benefits

  • Opportunity for significant career development in a fast-growing entrepreneurial environment.
  • High degree of individual responsibility and ownership.
  • Equal employment opportunity regardless of protected characteristics.

Interested in this position?

Apply directly on the company website

Apply Now

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