AI Field Engineer (Enterprise)

TL;DR

AI Field Engineer (Enterprise): Building and deploying production-ready generative AI systems for enterprise customers with an accent on inference foundations, model strategy, and fine-tuning. Focus on architecting scalable deployments, running load tests, and translating customer pain points into product improvements.

Location: Must be based in Singapore (On-site)

Salary: $200,000 - $350,000 SGD

Company

Fireworks AI is a Series C generative AI infrastructure company delivering industry-leading LLM inference speed and scalable model serving.

What you will do

• Build end-to-end POCs and MVPs alongside customer engineering teams within their specific codebases and infrastructure.
• Architect inference foundations and size deployments to ensure scalability without infrastructure bottlenecks.
• Deploy and validate new model families using inference frameworks like vLLM and SGLang.
• Guide customers on model selection, evaluation methodology, and fine-tuning strategies (SFT, DPO, RFT).
• Lead discovery conversations and maintain technical relationships from first engagement through production deployment.
• Translate recurring customer pain points into concrete product proposals and platform improvements.

Requirements

• 5+ years in a hands-on, customer-facing technical role such as Applied AI Engineer or Solutions Architect.
• Proven track record of shipping production software directly in customer environments.
• Strong Python skills and familiarity with Kubernetes and infrastructure engineering.
• Working knowledge of the LLM stack, including inference trade-offs and fine-tuning workflows.
• Experience with cloud infrastructure (AWS, Azure, GCP) and deploying models on GPU infrastructure.
• Exceptional communication skills for interacting with both ML engineers and executive stakeholders.

Nice to have

• 10+ years of technical field or engineering experience.
• Expertise in tuning deployments using vLLM, SGLang, or TensorRT-LLM.
• Experience with hyperscaler AI platforms like Azure AI Foundry, AWS Bedrock, or GCP Vertex AI.
• Experience building agentic systems, tool-use chains, or AI-native developer toolchains.

Culture & Benefits

• Opportunity to tackle hard problems at the forefront of AI infrastructure and low-latency inference.
• High ownership and impact in a fast-growing environment with minimal bureaucracy.
• Collaboration with world-class engineers and AI researchers from Meta and Google.
• Competitive salary, meaningful equity, and a comprehensive benefits package.