AI Field Engineers embed with customers and technology partners to turn complex AI problems into production systems, fast.
You will spend most of your time building, shipping code, running benchmarks, debugging production issues, and architecting deployments.
Lead discovery conversations, align stakeholders, and translate customer pain points into product improvements.
Work with innovative AI-native companies, building at the frontier where GenAI is core to their product.
Build end-to-end POCs and MVPs alongside customer engineering teams, navigating their codebases and infrastructure.
Help customers with model selection, fine-tuning strategy, and evaluation methodology.
Own the technical relationship from first engagement through production deployment, spending time on-site with customers.

5+ years in a hands-on, customer-facing technical role: Forward Deployed Engineer, Applied AI Engineer, Solutions Architect, ML Engineer with field exposure, or technical founder.
Demonstrated ability to build production software with customers, not just advise on it.
Strong Python skills.
Comfortable reading, writing, and debugging production code.
Familiarity with Kubernetes and infrastructure engineering.
Working knowledge of the LLM stack: inference trade-offs, model serving, fine-tuning workflows (SFT at minimum; DPO/RFT a strong plus).
Experience with cloud infrastructure (AWS, Azure, GCP) and deploying models on GPU infrastructure.
Exceptional communication.
Experience building or integrating agentic systems, tool-use chains, or AI-native developer toolchains.
10+ years in technical field or engineering roles (preferred)
Experience with inference serving frameworks (vLLM, SGLang, TensorRT-LLM) and tuning deployments for real workloads (preferred)
Prior experience at a company with a forward-deployed or embedded engineering model (Palantir, Scale AI, Anthropic, OpenAI, BCG X, McKinsey Quantum Black, AI Native startups with FDE motions) (preferred)
Prior experience as a technical founder or early engineer at an AI-native company is a strong signal (preferred)
Track record taking GenAI POCs from prototype to production-scale deployments (preferred)
Experience with hyperscaler AI platforms (Azure AI Foundry, AWS Bedrock/SageMaker, GCP Vertex) (preferred)

AI Field Engineer – AI Natives

Key skills