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Job Closed

Forward Deployed Software Engineer

  • Source: Naukri
  • Nexocean
  • $31,453.79 to $52,422.99 /yr
  • On-site
  • Bengaluru
  • Full-Time
  • Mid level

Job Description

Position Overview

  • We are looking for a Senior Forward Deployed Engineer (FDE) who is passionate about operationalizing production AI-native and agentic workloads at scale. This is a high-impact role designed to serve as the “technical tip of the spear” for most strategic AI-native customers and platform initiatives.
  • As an FDE, you will operate at the intersection of Product Engineering, AI Infrastructure, and Customer Implementation. You will partner deeply with strategic AI-native enterprises (ANEs), startups, infrastructure vendors, and internal engineering teams to deploy, optimize, and scale production AI systems on AI-Native Cloud.
  • This role extends beyond traditional GPU infrastructure deployment. You will work across Inference Engine, runtime systems, orchestration frameworks, and AI-native applications to help customers operationalize production AI and agentic systems with strong focus on scalability, reliability, latency, and workload economics.
  • FDE engineers also act as the “first customer” for new AI-native platform capabilities. You will validate products under real-world workloads, surface operational insights and architectural gaps, and help accelerate product maturity through continuous feedback loops with Product Engineering and Research teams.
  • You will build scalable deployment frameworks, benchmarking systems, automation tooling, and AI starter kits that transform field learning into reusable platform intelligence and repeatable deployment patterns across the ecosystem.
  • Your mission is to accelerate production adoption of AI-native systems while helping shape the future of DigitalOcean’s AI-Native Cloud for the inference and agentic era.

Preferred Qualifications

  • AI Infrastructure & Forward Deployed Engineering Experience: 4+ years of experience working in Forward Deployed Engineering, ML Engineer, Applied AI Engineer, AI Infrastructure, Technical Consulting, or equivalent customer-facing engineering roles supporting production AI systems.Platform Enablement & Ecosystem Experience:
  • Experience building deployment standards, technical enablement programs, platform adoption frameworks, or ecosystem integration strategies across customer-facing and engineering organizations.Open Source & AI Ecosystem Involvement: Active contributor to open-source AI, infrastructure, orchestration, or developer tooling ecosystems.Vendor & Strategic Partnership Collaboration:
  • Experience collaborating with GPU vendors, infrastructure providers, model vendors, or ecosystem partners on benchmarking, optimization, technical validation, or launch readiness initiatives.

Skills

  • operational-insights
  • digitalocean
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