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Solutions ArchitectFireworks AI • New York, New York, United States
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Solutions Architect

Fireworks AI
  • US
    New York, New York, United States
  • US
    New York, New York, United States
Jetzt Bewerben

Über

At Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest‑quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting‑edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI. In the last few months alone we've launched the Fireworks Training Platform, partnered with Microsoft Azure Foundry, and published research straight from our production systems which is helping scale some of the most innovative companies and products of our generation. As an SA you'll be close to all of it. The customer conversations you lead directly feed our roadmap, and the work you do shows up in what we build and publish next. A few examples of what that looks like in practice: If you want to work on hard infrastructure problems, be close to the customers pushing the frontier, and actually see your work ship come work with us! Role Solutions Architects at Fireworks are the technical and strategic owners of the customer relationship from the first discovery call through to production. You'll work with some of the most ambitious engineering teams in the world, translating complex business problems into concrete AI solutions built on the Fireworks platform. This is a role that demands both technical depth and strong people skills. You'll need to earn the trust of ML engineers and VPs in the same meeting, scope and execute POCs without losing sight of the customer's definition of success, and know enough about inference, fine‑tuning, and model architecture to make credible recommendations under pressure. Enterprise SA Track
Works with digital native and large organizations — navigating multiple stakeholders, procurement cycles, and executive relationships Heavy emphasis on executive presence: equally comfortable presenting to a CTO and debugging a latency issue with an ML engineer Owns the account relationship end‑to‑end, including expansion and renewal Strong commercial instincts understands how to build a business case and close large deals
Applied AI Track
Works with high‑velocity accounts and technology partners startups, ISVs, and hyperscaler ecosystems Heavier emphasis on technical execution more time in the code, building integrations, running enablements Faster iteration cycles with less org navigation focused on shipping working solutions quickly Embeds with partner engineering teams to enable their AI practices and build joint solutions Comfortable operating across engineering, partnerships, and sales simultaneously
What You'll Work On Technical Discovery & Solution Design
Lead structured discovery conversations to unpack customer pain points, constraints, and success criteria before proposing solutions Design end‑to‑end architectures for GenAI applications covering model selection, inference configuration, RAG design, and fine‑tuning strategy
POC Scoping & Execution
Define what a minimal, compelling proof‑of‑concept looks like and own it through to delivery. Prioritize and stack‑rank opportunities: manage scope creep, set realistic timelines, and keep the customer aligned on what success looks like Work alongside product and engineering teams to execute technically rigorous POCs
Performance Engineering
Run inference sweeps and establish performance baselines for customer workloads Create and configure deployments tuned to specific latency, throughput, and cost targets
Fine‑Tuning & Model Recommendations
Guide customers on fine‑tuning strategy and model recommendations: when to use SFT, DPO, or RFT, and which model family fits their use case Build and run fine‑tuning pipelines directly for customers Evaluate model quality and help customers build robust eval pipelines
Account Ownership & Stakeholder Management
Own the technical relationship across the account: from champion to executive sponsor Navigate complex organizations, build trust at multiple levels, and maintain momentum through long sales cycles Feed customer signal: deployment patterns, pain points, feature gaps — back into the product roadmap
What We're Looking For
5+ years in a technical, customer‑facing role — Solutions Architect, Sales Engineer, Forward Deployed Engineer, Customer facing AI Engineer / Data Scientist or equivalent Hands‑on experience with the LLM stack: inference trade‑offs, fine‑tuning methodologies (SFT, RFT, DPO), and deploying models at scale Strong Python skills: comfortable reading, writing, and debugging production code Exceptional communication: able to run a sharp discovery call, present to a VP, and explain reinforcement learning to an ML engineer in the same afternoon Experience with cloud infrastructure (AWS, Azure, GCP) and model serving at scale
Why Fireworks AI?
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. #J-18808-Ljbffr
  • New York, New York, United States

Sprachkenntnisse

  • English
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