AI Field Engineer - Enterprise
Fireworks AI- Location
- Location not stated
- Workplace
- Remote
- Employment
- Full Time
- Salary
- USD 200,000–260,000/yr
Posted 3mo ago
The employer’s full description could not be read from their board. This is a summary of the posting — follow the apply link for the original.
Responsibilities
- Build end-to-end POCs and MVPs alongside customer engineering teams
- Architect inference foundations for GenAI customers
- Size deployments for market scale
- Run load tests and tune deployments
- Deploy and validate new model families on inference frameworks
- Guide customers on model selection and fine-tuning strategy
- Build and run fine-tuning pipelines
- Design and implement evaluation frameworks
- Lead structured discovery conversations
- Own the technical relationship from first engagement through production deployment
- Identify recurring customer pain points and translate into product proposals
- Codify repeatable deployment patterns and contribute back to internal tooling
- Feed customer signals back into the product roadmap
Requirements
- 5+ years in a customer-facing technical role
- Demonstrated ability to build production software with customers
- Shipped code running in someone else's production environment
- Strong Python skills
- Comfortable reading, writing, and debugging production code
- Familiarity with Kubernetes and infrastructure engineering
- Working knowledge of the LLM stack
- Experience with cloud infrastructure (AWS, Azure, GCP)
- Experience deploying models on GPU infrastructure
- Exceptional communication skills
Preferred
- 10+ years in technical field or engineering roles
- Experience with inference serving frameworks (vLLM, SGLang, TensorRT-LLM)
- Experience tuning deployments for real workloads
- Experience operating as a technical authority inside a customer's environment
- Track record taking GenAI POCs from prototype to production-scale deployments
- Experience with hyperscaler AI platforms (Azure AI Foundry, AWS Bedrock/SageMaker, GCP Vertex)
- Experience building or integrating agentic systems, tool-use chains, or AI-native developer toolchains
Skills
- Python
- Kubernetes
- AWS
- Azure
- GCP
- vLLM
- SGLang
- TensorRT-LLM
- PyTorch
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