Senior Forward Deployed Engineer I (AI Infra)
Salary not listed • Bengaluru • Full-time
Posted 4mo ago
This job has been open for more than 60 days. It may no longer be actively hiring, so check with the company before putting a lot into an application.
About the job
We are seeking a Senior Forward Deployed Engineer (FDE) to join our AI Infrastructure team. In this role, you will work closely with strategic AI enterprises and high-growth startups, architecting, implementing, and fine-tuning production infrastructure on DigitalOcean's AI-Native Cloud. You will embed directly with customer engineering teams to solve complex infrastructure bottlenecks, optimize GPU cluster performance, and engineer critical inference and training platforms. Your mission is to accelerate the adoption of AI-native systems and shape the future of AI cloud infrastructure for the inference and agentic era.
Responsibilities
- Act as the primary technical authority on heterogeneous AI infrastructure for high-value customers, co-engineering custom GPU infrastructure solutions.
- Architect and fine-tune low-latency, high-throughput LLM serving platforms across NVIDIA CUDA and AMD ROCm platforms using various serving frameworks and model execution techniques.
- Deploy, scale, and manage resilient Kubernetes clusters tailored for compute-heavy AI workloads.
- Build scalable, repeatable infrastructure blueprints using Terraform, Ansible, and Helm to automate GPU provisioning, networking, and storage.
- Debug complex stack issues spanning host drivers, container runtimes, inter-GPU communication libraries, high-speed interconnects, and distributed storage systems.
- Translate common customer infrastructure challenges into core platform features, working with product and core infrastructure teams.
- Travel up to 30% for customer engagements, workshops, conferences, and internal collaboration.
- Consistently overlap with North American business hours for effective collaboration with customers and internal teams.
Requirements
- Expertise with Linux systems engineering, Kubernetes, and Infrastructure as Code (Terraform, Helm).
- Hands-on experience managing NVIDIA (CUDA, NCCL, NVLink, Triton) or AMD (ROCm, RCCL, CDNA) acceleration stacks.
- Experience with modern LLM serving frameworks (vLLM, TensorRT-LLM, Ray Serve) on CUDA and ROCm backends.
- Deep understanding of high-performance interconnects (RDMA, InfiniBand, RoCE, AMD Infinity Fabric™) and high-throughput storage systems.
- Strong proficiency in Python and Go; C++, CUDA C/C++, or AMD HIP is a major plus.
- 6+ years of experience in Forward Deployed Engineering, AI Infrastructure, or Technical Consulting roles supporting production AI systems.
- Ability to translate complex infrastructure concepts into engineering solutions and collaborate directly with client teams.
- Preference for delivering production-ready code, low-latency container images, and deployment blueprints.
- Comfort navigating fast-moving environments and tuning model workloads for diverse accelerator architectures.
- Experience collaborating with GPU vendors, infrastructure providers, or ecosystem partners.