Forward Deployed Engineer (Generative AI)

New

Tiger Analytics Inc.Advanced Analytics Consulting

United States. CanadaFull-TimeMiddle

Salary not disclosed

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Job Details

Required Skills: PythonCloud ComputingKubernetesPyTorchGoTerraformGenerative AI

Hands-on experience with LLM orchestration tools (LangChain, LlamaIndex, AutoGen) and deep learning frameworks (PyTorch, Hugging Face).
Production experience setting up and querying vector stores (Milvus, Pinecone, Qdrant, Chroma, or pgvector).
Proficiency in model serving frameworks (vLLM, TGI, Triton Inference Server) and evaluation tools.
Advanced knowledge of cloud AI primitives (AWS Bedrock/SageMaker, Azure OpenAI, GCP Vertex AI) and Kubernetes (K8s) for GPU workloads.
Mastery of Terraform or OpenTofu to provision complex multi-cloud compute environments.
Strong coding skills in Python (preferred) or Go, with an emphasis on writing clean, concurrent code.
Ability to manage customer expectations around LLM non-determinism, hallucinations, and performance trade-offs.
Willingness to travel to client sites to lead high-stakes, on-site deployment sprints.

Deploy, fine-tune, and optimize large-scale Gen AI models and LLM orchestration frameworks within customer cloud environments.
Architect scalable infrastructure for AI workloads utilizing 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 agnostic, resilient cloud deployments across AWS, Azure, and GCP using Infrastructure as Code (IaC).
Act as the primary technical consultant, guiding enterprise clients through AI safety, prompt engineering patterns, and inference cost optimization.
Feed edge-case deployment insights back to core AI research and platform engineering teams to improve product robustness.

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