AI Field Engineer - AI Natives
Remote • San Mateo • FullTime
Posted 3mo ago
Remote Work Policy
Fully remote
Employment Type
FullTime
Categories
Applied AI Engineer
About the job
Fireworks is seeking an AI Field Engineer to join their team. This role is at the forefront of technical engagement, embedding with ambitious customers and technology partners to rapidly transform complex AI challenges into production systems. You will operate at the intersection of engineering, product, and customer delivery, taking a hands-on approach to building Proofs of Concept (POCs), Minimum Viable Products (MVPs), and production integrations. Simultaneously, you will engage in executive-level discussions on architecture, strategy, and business outcomes. The position requires a significant amount of hands-on work, including shipping code, running benchmarks, debugging production issues, and architecting deployments, alongside leading discovery conversations, aligning stakeholders, and translating customer needs into product improvements.
Responsibilities
- Build end-to-end POCs and MVPs within customer codebases, infrastructure, and constraints.
- Architect inference foundations for customers whose core product is built on GenAI and size deployments for scalability.
- Run load tests, establish performance baselines (latency, throughput, cost), and tune deployments.
- Deploy and validate new model families on inference frameworks, optimizing configurations and serving patterns.
- Guide customers on model selection, fine-tuning strategies (SFT, DPO, RFT), and evaluation methodologies.
- Build and run fine-tuning pipelines with customers, managing trade-offs between model families, compute cost, and quality.
- Design and implement evaluation frameworks for production-quality metrics.
- Help customers integrate frontier model capabilities into their core offerings for a competitive edge.
- Lead discovery conversations to understand customer pain points, constraints, and success criteria.
- Own the technical relationship from initial engagement through production deployment, embedding as a peer.
- Spend time on-site with customers to build trust and momentum.
- Identify recurring customer pain points and translate them into product proposals for engineering and product teams.
- Codify repeatable deployment patterns for internal tooling, documentation, and the platform.
- Provide specific and urgent feedback on customer signals to the product roadmap.
Requirements
- 5+ years in a hands-on, customer-facing technical role (e.g., Forward Deployed Engineer, Applied AI Engineer, Solutions Architect, ML Engineer with field exposure, or technical founder).
- Demonstrated ability to build production software with customers and ship code running in their production environments.
- Strong Python skills, with proficiency in reading, writing, and debugging production code.
- Familiarity with Kubernetes and infrastructure engineering.
- Working knowledge of the LLM stack, including inference trade-offs, model serving, and fine-tuning workflows (SFT minimum; DPO/RFT a plus).
- Experience with cloud infrastructure (AWS, Azure, GCP) and deploying models on GPU infrastructure.
- Exceptional communication skills for discovery calls and executive presentations.