AI Field Engineer, EMEA
London • FullTime
Posted 1mo ago
Remote Work Policy
On-site
Employment Type
FullTime
Categories
Applied AI Engineer
About the job
Fireworks is seeking an AI Field Engineer to join our team in EMEA. This role is at the forefront of our technical engagement with ambitious customers and technology partners, focusing on transforming complex AI challenges into production-ready systems. You will operate at the intersection of engineering, product, and customer delivery, actively building Proofs of Concepts (POCs), Minimum Viable Products (MVPs), and production integrations. This position requires a blend of hands-on technical execution and the ability to engage in executive-level discussions regarding architecture, strategy, and business outcomes. The role emphasizes building strong relationships and trust through in-person interactions with clients, particularly within large organizations and digital-native companies adopting GenAI.
Responsibilities
- Build end-to-end POCs and MVPs with customer engineering teams, integrating into their codebases and infrastructure.
- Architect inference foundations for customers whose core products are GenAI-based, ensuring scalable deployments.
- Run load tests and establish performance baselines (latency, throughput, cost) for customer traffic profiles, tuning deployments accordingly.
- Deploy and validate new model families on inference frameworks like vLLM and SGLang, optimizing configurations for various workloads.
- 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 targets.
- Design and implement evaluation frameworks to measure production-quality metrics.
- 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 to build trust and momentum through in-person collaboration.
- Identify recurring customer pain points and translate them into actionable 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).
- Proven ability to build production software with customers, with experience shipping code in a customer's production environment.
- Strong Python skills, including 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.