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Forward Deployed Engineer (Generative AI)

3 days, 21 hours ago
United States, Canada
Full-time
Senior
AI Engineer
Software Development
AWS Azure GCP Generative AI Go Hugging Face Kubernetes LLM Machine Learning Python PyTorch 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 37

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.
  • Collaborate with customer engineering teams to integrate AI systems into production-grade cloud infrastructure.
  • Feed deployment insights and edge cases back to internal research and platform engineering teams to improve product robustness.
  • Manage on-site deployment sprints and work directly with clients during implementation.
  • Support technical problem-solving across the stack, from GPU drivers to prompt engineering logic.

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 setting up and querying vector stores 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 cloud AI services such as AWS Bedrock/SageMaker, Azure OpenAI, or GCP Vertex AI.
  • Experience using Kubernetes for GPU workloads.
  • Mastery of Terraform or OpenTofu for provisioning complex multi-cloud compute environments.
  • Strong coding skills in Python, preferably, or Go.
  • 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.

Benefits

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

Interested in this position?

Apply directly on the company website

Apply Now

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