Staff Forward Deployed Engineer, AI/ML

digitalocean98

United States

Hybrid

USD 220,000 - 239,000

Full time

14 days+

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Benefits offered by this job

Hybrid role
Bonus & equity eligibility

Job summary

digitalocean98 seeks a Staff Forward Deployed Engineer to lead AI-native customer deployments and platform initiatives. The role sits at the crossroads of product engineering, AI infra, and customer implementation, guiding strategic clients to production AI and agentic systems.

You will validate new platform capabilities as an early customer, collaborating with teams across engineering and partnerships, and traveling up to 30% for engagements and events.

Qualifications

  • Experience in Forward Deployed Engineering, AI Infrastructure, Technical Consulting, or AI Platform Engineering supporting production AI systems.
  • Proven ability to benchmark and optimize AI infrastructure for scalability, reliability, GPU efficiency, and latency.

Responsibilities

  • Partner with strategic AI-native enterprises and startups to architect, deploy, and scale production AI and agentic systems.
  • Optimize distributed inference and runtime performance through benchmarking, GPU efficiency tuning, KV-cache optimization, speculative decoding, and latency and cost optimization.
  • Act as the first customer for new AI-native platform capabilities, surfacing operational insights to product engineering and research teams.
  • Build scalable deployment assets including benchmarking systems, automation tooling, AI starter kits, and reference architectures.
  • Collaborate with GPU vendors, model providers, infrastructure partners, and ISVs on co-development, validation, and launch readiness.
  • Travel up to 30% for customer engagements, workshops, ecosystem partnerships, and conferences

Skills

Forward Deployed Eng
AI Infrastructure
Technical Consulting
AI Platform Eng
Production AI

Job description

Role overview

A hybrid Staff Forward Deployed Engineer role serving as the technical lead for AI-native customers and platform initiatives. The position operates at the intersection of product engineering, AI infrastructure, and customer implementation, helping strategic clients deploy and scale production AI and agentic systems, and validating new platform capabilities as the first customer.

Responsibilities
  • Partner with strategic AI-native enterprises and startups to architect, deploy, and scale production AI and agentic systems
  • Optimize distributed inference and runtime performance through benchmarking, GPU efficiency tuning, KV-cache optimization, speculative decoding, and latency and cost optimization
  • Act as the first customer for new AI-native platform capabilities, surfacing operational insights to product engineering and research teams
  • Build scalable deployment assets including benchmarking systems, automation tooling, AI starter kits, and reference architectures
  • Collaborate with GPU vendors, model providers, infrastructure partners, and ISVs on co-development, validation, and launch readiness
  • Travel up to 30% for customer engagements, workshops, ecosystem partnerships, and conferences
Requirements
  • Experience in Forward Deployed Engineering, AI Infrastructure, Technical Consulting, or AI Platform Engineering supporting production AI systems
  • Strong understanding of workflow orchestration, deployment systems, memory patterns, and AI-native application architectures
  • Production coding skills in Python or Go with experience building tooling, automation systems, and benchmarking frameworksProven ability to benchmark and optimize AI infrastructure with focus on scalability, reliability, GPU efficiency, and latency
  • Consultative execution skills with the ability to establish technical credibility with CTOs and Principal architects
  • Active contributor to open-source AI, infrastructure, orchestration, or developer tooling ecosystems
Nice to have
  • Experience collaborating with GPU vendors, infrastructure providers, or model vendors on benchmarking and launch readiness initiatives
Benefits and work setup
  • Hybrid role
  • Compensation range of $220,000 - $239,000
  • Eligibility for bonus and equity compensation
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