GenAI Systems Architect — LLMs, RAG & Production

Onebyzero; Singapore; On-site; SGD 180,000 - 260,000; Full time

Job summary

Onebyzero in Singapore is seeking a Deep Learning Architect with 4+ years to design production-grade GenAI systems, focusing on end-to-end LLM architectures, RAG pipelines, and multi-agent setups with strong production readiness.

You will translate client requirements into model adaptation strategies, review designs, optimise latency and cost, and collaborate with engineering and data teams to deliver high-impact GenAI solutions.

Qualifications

• 3–6 years of ML engineering/LLM experience with production focus.
• Hands-on experience with CPT, SFT, LoRA or QLoRA on LLMs.
• Strong Python programming for production-grade code.
• Experience deploying models to cloud with cost and latency awareness.
• Ability to translate client requirements into model adaptation strategies.

Responsibilities

• Design and contribute to end-to-end LLM system architecture for real-world enterprise use cases.
• Pre-train, fine-tune LLMs and domain models using CPT, SFT, LoRA, QLoRA.
• Build evaluation pipelines to benchmark performance, accuracy, and cost.
• Optimise latency, throughput, token efficiency, and inference cost in production.
• Integrate fine-tuned models into multi-agent pipelines with orchestration teams.
• Implement prompt versioning, rollback strategies, and model monitoring.
• Translate business requirements into model adaptation strategies with clear success criteria.
• Contribute to internal knowledge sharing on fine-tuning practices and tooling.
• Define enterprise patterns for GenAI systems: identity, governance, and data boundaries.

Tools

Bedrock

OpenSearch

Lambda

ECS/EKS

Pinecone

Weaviate

Milvus

Docker

Kubernetes

Job description

Onebyzero in Singapore is seeking a Deep Learning Architect with 4+ years to design production-grade GenAI systems, focusing on end-to-end LLM architectures, RAG pipelines, and multi-agent setups with strong production readiness.

You will translate client requirements into model adaptation strategies, review designs, optimise latency and cost, and collaborate with engineering and data teams to deliver high-impact GenAI solutions.