Fireworks AI is seeking an AI Field Engineer for Strategic Partnerships to lead technical relationships and drive enterprise AI transformation from San Mateo or remotely. This full-time role suits an experienced engineer with a passion for bridging the gap between cutting-edge machine learning technology and large-scale partner ecosystems.
Role Overview
As an AI Field Engineer for Strategic Partnerships, the candidate acts as one of the primary technical owners for key strategic relationships at Fireworks AI. Working alongside partner field teams, Independent Software Vendors (ISVs), and Systems Integrators (SIs), this position makes Fireworks the default inference and fine-tuning layer across major architectures. The role blends engineering, partner enablement, and customer delivery. Responsibilities include building reference architectures, executing benchmarks, debugging live production integrations, and co-developing proofs of concept while engaging in executive-level strategic discussions.
Key Responsibilities
Lead technical co-sell motions with Strategic Partners by creating joint reference architectures, integration patterns, and shared proofs of concept for target accounts.
Build end-to-end proofs of concept and minimum viable products directly inside partner codebases, infrastructure, and constraints.
Run comprehensive load tests to establish throughput, cost, and latency baselines against realistic customer traffic profiles, tuning deployments to hit performance targets.
Deploy and validate new model families across inference frameworks to determine optimal shapes, serving patterns, and quantization configurations.
Guide customers and partners through model selection, evaluation methodologies, and fine-tuning strategies including SFT, DPO, and RFT.
Build and execute fine-tuning pipelines directly with clients while balancing trade-offs between compute costs, quality targets, and model families.
Design and implement evaluation frameworks focused on production-quality metrics rather than simple benchmark scores.
Surface partner-driven product gaps to the internal engineering team and translate product roadmaps back into effective partner messaging.
Author external technical content such as reference architectures, integration guides, and benchmark blog posts.
Track pipeline health on a weekly basis, proactively flagging operational risks and business opportunities to field leadership.
Requirements
Minimum of 3 years of professional experience in a technical consulting, forward-deployed engineering, partner engineering, or pre-sales role.
Demonstrated ability to build production software with clients and ship code that runs reliably in external production environments.
Strong coding skills in Python, with the ability to comfortably read, write, and debug production code alongside familiarity with infrastructure engineering and Kubernetes.
Hands-on fluency with Large Language Model inference, encompassing batching strategies, quantization, structured outputs, function calling, and latency or throughput trade-offs.
Practical experience with model fine-tuning, requiring at least LoRA proficiency and a strong understanding of supervised fine-tuning limitations.
Deep familiarity with the Azure AI stack, including Azure Foundry, Azure ML, Azure OpenAI Service, AKS, and Entra or RBAC protocols for AI workloads.
Exceptional communication skills to lead discovery calls, present to vice presidents, and debug complex latency issues with machine learning engineers.
Nice to Have
5 or more years of experience in technical field or engineering roles owning formal technical relationships with hyperscalers or major systems integrators.
Familiarity with popular inference serving frameworks like vLLM, SGLang, and TensorRT-LLM.
Previous background working at an AI-native cloud provider, hyperscaler, or inference vendor.
Broad familiarity with alternative strategic partner platforms, networking, and identity integration patterns.
Experience utilizing agentic frameworks such as LangChain, LlamaIndex, or custom tool-use pipelines.
Background in rigorous model evaluation and a track record of authoring widely read technical blog posts or reference architectures.
Proven history of taking generative AI proofs of concept from early prototyping stages all the way to production-scale enterprise deployments.
Skills and Tools
Python
PyTorch
Azure
Kubernetes
LLM Inference Frameworks
LangChain
Salary and Benefits
On-target base salary ranging from $200,000 to $260,000 USD per year.
Meaningful equity in a fast-growing startup environment.
Comprehensive benefits package.
Base compensation is determined by individual qualifications, market data, location, skills, and interview performance.
About the Company
Fireworks AI is the platform for specialized intelligence, enabling companies to build, train, and serve AI models tailored to their unique data, workflows, and products. Founded by the original team behind PyTorch and backed by prominent investors like Sequoia Capital, Benchmark Capital, and NVIDIA, the Series D company powers production AI across text, image, audio, embedding, and multimodal workloads.
How to Apply
Interested candidates should visit the official Fireworks AI careers page to submit an application for this remote or San Mateo-based position.
