Senior Forward Deployed Engineer I (AI/ML)
DigitalOcean3 months ago
Bengaluru, IndiaSenior
Responsibilities
- Architect, deploy, optimize, and scale production AI and agentic systems for strategic customers and AI startups on DigitalOcean’s AI-Native Cloud.
- Support complex migrations, production-ready proofs of concept, deployment acceleration, and long-term workload expansion across inference and runtime platforms.
- Optimize distributed inference and runtime performance through benchmarking, GPU efficiency tuning, KV-cache optimization, speculative decoding, prefill/decode disaggregation, and multi-node deployments.
- Validate AI-native platform capabilities as a first customer and communicate operational insights, architectural gaps, and scaling bottlenecks to Product Engineering and Research teams.
- Build deployment frameworks, benchmarking systems, automation tooling, AI starter kits, fine-tuning workflows, operational playbooks, and reference architectures.
- Collaborate with GPU vendors, model providers, infrastructure partners, and ISVs on co-development, technical validation, optimization, and launch readiness.
- Enable customer-facing technical and partner teams through deployment patterns, benchmarking insights, playbooks, reference architectures, demos, and technical guidance.
- Travel for customer engagements, strategic workshops, conferences, and internal collaboration as needed.
Requirements
- Experience designing and operationalizing production AI systems, including inference workloads, agentic runtimes, orchestration frameworks, and AI-native applications.
- Hands-on experience with inference and serving frameworks such as vLLM, SGLang, Ray Serve, NVIDIA Dynamo, or llm-d, plus LLM optimization techniques including continuous batching, quantization, KV-cache optimization, and speculative decoding.
- Deep expertise with NVIDIA and AMD GPU platforms and ecosystems including CUDA, ROCm, TensorRT, Triton, NCCL, RCCL, NVLink, XGMI, and RoCE.
- Strong proficiency with Kubernetes, distributed systems, networking, storage systems, Infrastructure as Code, and large-scale AI infrastructure architectures.
- Experience with AI orchestration and agent frameworks such as LangGraph, CrewAI, MCP ecosystems, LlamaIndex, and OpenAI Agents SDK.
- Strong production coding skills in Python or Go, including tooling, automation systems, deployment workflows, benchmarking frameworks, and operational platforms.
- Ability to benchmark and optimize AI infrastructure for scalability, reliability, GPU efficiency, runtime performance, latency, and workload economics.
- Ability to establish technical credibility with CTOs, principal architects, product engineering teams, and ecosystem partners while managing high-impact deployments and initiatives.
- 4+ years of experience in Forward Deployed Engineering, ML Engineering, Applied AI Engineering, AI Infrastructure, Technical Consulting, or equivalent customer-facing engineering roles supporting production AI systems.
- Experience building deployment standards, technical enablement programs, platform adoption frameworks, or ecosystem integration strategies.
- Active contribution to open-source AI, infrastructure, orchestration, or developer tooling ecosystems is preferred.
- Experience collaborating with GPU vendors, infrastructure providers, model vendors, or ecosystem partners on benchmarking, optimization, technical validation, or launch readiness is preferred.
Benefits
- Hybrid role located in Bengaluru, India.
- Travel up to 30% is required, with consistent overlap with North American business hours through at least noon Eastern Time.
- Reimbursement for relevant conferences, training, and education.
- Access to LinkedIn Learning courses.
- Employee Assistance Program, local employee meetups, and flexible time off.
- Eligible employees may receive equity compensation and participate in the Employee Stock Purchase Program.
Tech Stack
Categories
Forward Deployed
About DigitalOcean
DigitalOcean provides cloud infrastructure and platform services for developers, startups, and small to mid-sized businesses, including virtual machines (Droplets), managed Kubernetes and databases, object/block storage, networking, and GPUs for AI workloads. It operates a usage-based, self-service public cloud with APIs, CLI, and a marketplace to deploy and scale applications. Founded in 2012 and headquartered in Broomfield, Colorado, DigitalOcean is a public company listed on the NYSE.