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Solution Architect (AI/LLM Inference)

165k – 330kSan Francisco, CANew York, NYSolutions ArchitectureHybrid
Summary

Partners with Sales to conduct technical discovery, lead demos, scope AI/LLM inference deployments, and manage POCs for customers adopting AI at scale. Requires AI/ML expertise, customer-facing skills, and ability to prototype solutions.

About the role

Responsibilities

  • Partner with Sales on customer discovery calls (most often second calls, occasionally first calls for large accounts).
  • Lead demos and technical scoping to align on success criteria, architecture, and deployment approach.
  • Own benchmarking and repeatable deployments, including:
    • Handling standard deployment patterns and configurations across many modalities – LLMs, embeddings, image and video generation, VoiceAI, etc.
    • Advising on tradeoffs like H100s vs B200s and latency-optimized vs throughput-optimized setups.
    • Driving consistent "playbook" style deployments for common models and use cases.
  • Become a power user of different runtimes such as vllm, sglang, and TRT-LMM and all the common configurations and tradeoffs between them.
  • Drive POC and project execution, including:
    • Scoping POCs and keeping stakeholders aligned on timeline, deliverables, and next steps.
    • Acting as the "ringleader" or project manager for POCs.
    • Pulling in Forward Deployed Engineering (FDE) support when deeper or more complex technical work is needed.

Requirements

  • AI/ML background and the ability to credibly discuss AI/ML topics with technical stakeholders.
  • Strong customer-facing communication skills, including the ability to run structured discovery and clarify ambiguous requirements.
  • Technical depth to scope solutions, without needing to write production code.
  • Ability to script and prototype as needed, including comfort "vibe coding" to move quickly in technical workflows.

Nice to Have

  • Experience running or supporting benchmarks for ML inference deployments.
  • Familiarity with infrastructure tradeoffs relevant to inference performance and cost (for example GPU selection and latency versus throughput tuning).
  • Experience serving as a cross-functional technical lead for customer POCs, including coordination across Sales and Engineering.

Benefits

  • Competitive compensation, including meaningful equity.
  • 100% coverage of medical, dental, and vision insurance for employee and dependents.
  • Flexible PTO policy including company wide Winter Break (offices closed from Christmas Eve to New Year's Day).
  • Paid parental leave.
  • Fertility and family-building stipend through Carrot.
  • Company-facilitated 401(k).
  • Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities.
Skills
AI/MLLLMsvLLMsglangTRT-LLMGPUH100B200embeddingsinferencebenchmarksPythonscripting
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