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Fireworks

AI Forward Deployed Engineer EMEA

London
Posted about 23 hours ago
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About Us:

Fireworks is the platform for specialized intelligence, enabling companies to build, train, and serve AI models tailored to their own data, workflows, and products. Founded by the team behind PyTorch and backed by AMD, Atreides, Benchmark Capital, Index Ventures, Lightspeed, NVIDIA, Sequoia Capital, and TCV, Fireworks powers production AI with hundreds of state-of-the-art open models across text, image, embedding, audio, and multimodal workloads. Today, Fireworks is a Series D company valued at $17.5 billion, bringing together an ambitious, collaborative team that's building the future of enterprise AI.

The Role:

As an AI Forward Deployed Engineer, you are the technical owner of a customer deployment. You embed with a small number of accounts, write code in their environment, and unblock whatever stands between them and production on Fireworks: capacity, model selection, integration, latency, cost. You scope high-stakes deals before signature and then deliver what you scoped. This role suits engineers with a founder CTO mentality who genuinely enjoy customer work.

What we value most is first principles thinking: reasoning about unfamiliar problems from the ground up rather than from playbooks. You will be evaluated on this directly in the interview process, and strength here can outweigh gaps elsewhere in your background.

Key Responsibilities:

  • Deployment Ownership: Own the technical outcome of customer deployments end to end, from architecture through production.
  • Embedded Pilots: Design, scope, and run proof-of-value pilots inside customer environments, with clear success criteria.
  • Pre-Signature Scoping: Act as the technical owner on complex deals (dedicated deployments, BYOC, compliance-sensitive architectures) and carry them through delivery.
  • Unblocking: Diagnose and resolve capacity, performance, integration, and model selection issues, pulling in specialists where needed.
  • Model and Platform Fit: Guide customers to the right models, deployment tiers, and optimization paths (e.g. quantization, speculative decoding, fine-tuning handoff to AMLEs).
  • Product Signal: Feed structured, prioritized signal from the field back to product and engineering.

Reasons to use Rodeo

I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?

Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.

Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.

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Graduate Consultant — 2026 Scheme

PwC·London, UK
£35,000/yr

Why you're a good match

Strong

Your economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.

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Why you're a good match

You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.

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Strong

Experience fit

Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.

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Minimum Requirements:

  • First principles and critical thinking: the ability to break down novel problems and reason to a solution without a reference implementation. This is the primary interview signal and can outweigh other qualifications.
  • Bachelor's degree in Computer Science, Engineering, or a related technical field.
  • 3+ years of experience as a software engineer, with depth in backend systems and infrastructure.
  • Strong coding skills in Python and at least one systems language; comfortable shipping in unfamiliar codebases and customer environments.
  • Fluent in AI-assisted and agentic engineering: uses coding agents and AI tooling as a core part of how you build, and knows when to trust the output and when not to.
  • Working knowledge of modern generative AI: inference, serving, and the tradeoffs across models and deployment options.
  • Proven ability to own ambiguous technical problems under time pressure and drive them to resolution.
  • Genuine appetite for customer-facing work and strong communication with senior technical stakeholders.

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Preferred Qualifications:

  • Founder or founding engineer experience, especially as a technical co-founder or CTO.
  • Experience with GPU infrastructure, distributed serving, or performance engineering.
  • Prior forward deployed, solutions architecture, or professional services experience at a technical product company.
  • Experience in a startup or fast-paced environment.

Why Fireworks?

  • Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.
  • Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.
  • Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.
  • Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.

Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.

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Skills

Python
Backend systems
Infrastructure
Generative AI
Inference
Model serving
Quantization
Speculative decoding
Fine-tuning
GPU infrastructure
Distributed serving
Performance engineering
Problem solving
Communication
Technical architecture

Location

London, England, United Kingdom

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