Role: Technical Program Manager (AI)

Function: Technical Program Management

Location: Bengaluru, India

Industry: AI infrastructure, Cloud 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 drive end-to-end programs that power the client’s AI inference platform, model registry, and developer tooling. You turn ambitious platform goals into clear roadmaps, milestones, and success metrics while setting the gold standard for delivery practices in a fast-growing deep-tech environment. Your work directly influences how enterprises deploy AI workloads at scale and positions you for significant ownership and visibility with senior leadership.

Role & Responsibilities

• Run end-to-end programs for the inference platform, AI tooling, and model registry.
• Translate business and platform goals into clear requirements, milestones, and success metrics.
• Standardize delivery practices, including planning, status reporting, post-mortems, and OKRs, for the AI vertical.
• Report program status to leadership with data on adoption, performance, and reliability.

Must have Criteria

• Experience in technical program management or adjacent technical roles (backend, ML, infrastructure) within a product environment.
• Working knowledge of ML workflows, model deployment, and inference architectures.
• Experience with cloud platforms and containerized services.
• Exposure to Terraform or similar infrastructure-as-code tools.

Nice to Have

• Experience with MLOps stacks or model serving platforms.
• Familiarity with developer tools or platform APIs.
• Startup or high-growth environment experience.