DevOps Engineer | SDE - 1 | SDE - 2

Preferable Location(s):

Pune, India | Mumbai, India | Chennai, India | Delhi, India | Hyderabad, India

Work Type:

Full Time

Salary Range:

$65K - $70K

Apply Now

Role: Technical Program Manager (Compute)

Function: Technical Program Management

Location: Bengaluru

Industry: AI infrastructure, Cloud Computing, High-Performance Computing

About Company

This role is with a rapidly growing AI infrastructure startup founded in 2025 in Bengaluru by a leadership team with deep product, cloud, and systems experience from global-scale tech companies. The company has built a GenAI-powered private cloud platform that automates and manages complex AI workloads across hybrid, on-prem, edge, and sovereign cloud environments — designed for enterprise sectors where performance, data security, and compliance are critical. Backed by leading global VCs and prominent operators (approx. $10M seed raised), the company is recognized for strong engineering rigor and product clarity. Its platform focuses on AI-native orchestration, deep observability, and cost/performance optimization to help large enterprises deploy and scale AI with confidence. This is an opportunity to join early and shape the future of AI-first cloud infrastructure.

Position Overview

You own critical compute programs that bring GPU-powered cloud services to life. You orchestrate cross-functional teams to ship vGPU, partitioning, and cluster bootstrapping features that unlock high-performance AI workloads for enterprise users.

Role & Responsibilities

Run end-to-end programs for VM templates, cluster bootstrap, and add-on codification.
Drive delivery of vGPU and GPU partitioning features.
Define program plans, milestones, and success metrics; track risks and dependencies across teams.
Standardize program hygiene, including PRDs or program briefs, status reports, and post-incident reviews.

Must have Criteria

Proven experience in technical program management or technical delivery roles focused on infrastructure, platform, or distributed systems.
Working knowledge of Kubernetes, virtualization, and GPU or accelerated compute concepts.

Nice to Have

Exposure to GPUaaS, HPC, or model-inference platforms.
Experience with capacity planning and observability for GPU or compute platforms

FAQs

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