AI ENGINEER

Helius Technologies Pte Ltd.

Singapore, Robinson

5-8 Years

SGD 1.02 - 1.14 LPA

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Job Description

Role Overview

We are seeking a Technical Lead to own the end-to-end strategy, architecture, and operations of a production-grade LLM inference platform. This role spans commercial partnership management, distributed systems engineering, and platform automation - owning everything from GPU cluster architecture to go-to-market execution on third-party marketplaces.

Key Responsibilities

Platform & Partnership Leadership

Lead end-to-end launch strategy for LLM inference channels on external marketplaces (e.g., OpenRouter), including business case development, pricing strategy, and partner relationship management
Own vendor and partner relationships, including routine reviews and pricing negotiations for the inference stack
Scale channel throughput to production volumes exceeding 10B+ tokens/day

Infrastructure & Platform Engineering

Design and build custom Kubernetes Operators (CRDs + controllers) to manage LLM inference deployments and benchmark runs as declarative, first-class cluster resources
Automate model provisioning, GPU placement, and scaling so new models move from config commit to serving traffic without manual intervention
Architect and operate multi-node distributed inference deployments over InfiniBand
Implement KV-cache reuse and disaggregated prefilling (e.g., LMCache) to drive significant throughput gains (1.6×+)
Build GPU autoscaling systems (e.g., KEDA-based) tied to real-time load signals

Performance & Capacity Planning

Build reproducible benchmarking systems (e.g., on NVIDIA aiperf) exposed as first-class CRDs across the GPU fleet
Define and measure sustainable throughput per (model, chip) under strict latency SLAs (e.g., TTFT 5s)
Translate benchmark data and marketplace pricing into break-even tokens/day and required per-replica TPS to drive GPU capacity planning decisions

Observability & Operations

Build observability systems covering TTFT, TPS, and per-API-key latency across the fleet
Design and deploy AI-driven operations agents (built on in-house multi-tenant agent runtimes) for automated anomaly detection and root-cause analysis, integrating Prometheus triggers and custom MCP tools
Drive incident resolution at scale, resolving hundreds of production incidents

Qualifications

Proven experience architecting and operating distributed GPU inference infrastructure at production scale
Hands-on expertise with Kubernetes Operator development (CRDs, custom controllers)
Deep familiarity with LLM serving optimization techniques (KV caching, disaggregated prefilling, autoscaling)
Experience with performance benchmarking and capacity planning for GPU workloads
Track record of owning commercial partnerships and pricing strategy for technical platforms
Experience building or integrating AI agent systems for operational automation
Strong cross-functional leadership: comfortable operating across infrastructure, product, and business strategy.

Important Note:

Please share your resume in word format with [Confidential Information]

Important Note: If this requirement is not a match for you please refer to your friends.

Interested professionals can reach out to me for Confidential Discussion @ +65- 9060-4050.

Best Regards,

Dilip Kumar Daga

Vice President - Strategic Accounts

Helius Technologies Pte Ltd

36, Robinson Road,#13-05, City House, Singapore 068877

DID: +(65) 6429-9407

Mobile: +(65) 9060-4050

Fax: +(65) 62222213