AI Field Engineer - Enterprise
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 crucial for 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 regarding architecture, strategy, and business outcomes. The position involves significant coding, running benchmarks, debugging production issues, and architecting deployments, alongside leading discovery conversations, aligning stakeholders, and translating customer needs into product improvements. This role requires comfort working on-site with customers to build relationships and trust in person.
Responsibilities
- Build end-to-end POCs and MVPs with customer engineering teams within their existing codebases, infrastructure, and constraints.
- Architect inference foundations for customers whose core products are GenAI-based, ensuring scalable deployments without infrastructure bottlenecks.
- Run load tests and establish latency, throughput, and cost baselines against realistic customer traffic profiles, tuning deployments to meet targets.
- Deploy and validate new model families on inference frameworks like vLLM and SGLang, optimizing configurations and serving patterns.
- Guide customers on model selection, fine-tuning strategies (SFT, DPO, RFT), and evaluation methodologies.
- Build and execute fine-tuning pipelines with customers, balancing model families, compute costs, and quality objectives.
- Design and implement evaluation frameworks to measure 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, building trust with both ML engineers and VPs.
- Spend time on-site with customers, embedding with their teams 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, with experience shipping code to 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, capable of leading discovery calls, presenting to VPs, and debugging technical issues.