AI Systems Engineer (Data Platform & Infrastructure)

DECIATO PTE. LTD.; Singapore; On-site; SGD 60,000 - 80,000; Full time

Job summary

A leading technology firm in Singapore is seeking an AI Systems Engineer to design and build their core cloud infrastructure. Responsibilities include managing Kubernetes environments, implementing SaaS architecture, and engineering data ingestion pipelines. The ideal candidate has experience with CI/CD, cloud-native technologies, and has a proactive startup mentality. Competitive compensation and dynamic work environment offered.

Qualifications

• Multiple years of hands-on experience with cloud-native infrastructure.
• Experience building and maintaining robust CI/CD pipelines.
• Deep expertise in MLOps and SaaS platforms.

Responsibilities

• Design, build, and manage infrastructure on Kubernetes.
• Implement multi-tenant secure service architecture.
• Engineer real-time data ingestion pipelines for various sectors.

Skills

Kubernetes

Terraform

CI/CD pipelines

Data engineering

Python

Tools

Kafka

Spark

Databricks

Snowflake

Job description

The Role: Architecting the Cognitive Platform

We are seeking a foundational AI Systems Engineer to design, build, and own the core infrastructure that powers our entire company.

This is a unique, high-leverage role. You are not just supporting one product; you are building the single, unified platform that must serve two critical functions:

1. Our SaaS Platform: A scalable, multi-tenant, and low-latency infrastructure that delivers our Causal AI models to paying customers via robust APIs/UI.
2. Our AI Research Platform: A high-performance, flexible environment that empowers our researchers to conduct massive "self-play" simulations, run "hero training runs" on vast, multimodal datasets, and rapidly prototype new models.

Your work will be the backbone that connects our most advanced research with real-world, high-stakes industrial data.

What You Will Do

• Build the Core Cloud-Native Platform: Design, build, and manage our entire infrastructure from the ground up on Kubernetes (K8s), using Infrastructure as Code (Terraform, Pulumi) for everything.
• Engineer the SaaS Delivery Architecture: Implement the multi-tenant, secure, and highly-available service architecture for our customer-facing APIs. This includes API gateways, service mesh, observability, and logging.
• Create the MLOps/Research Engine: Build the internal AI/ML platform. This includes managing data versioning (DVC, Pachyderm), orchestrating on-demand GPU/TPU-heavy training workloads, and providing researchers with feature stores and a "self-service" environment for experimentation.
• Master Real-Time Data & Orchestration: Engineer the high-throughput, real-time data ingestion pipelines (e.g., Kafka, Pulsar, Spark Streaming) required to model "network cascades" and "perishable inventory" in sectors like aviation and logistics.
• Own Complex Dataflow (DAGs): Design, implement, and manage the complex dataflow orchestration (e.g., Airflow, Dagster, Prefect) that powers both our production ETL/ELT and our complex, multi-stage AI simulation and training loops.
• Champion CI/CD & GitOps: Own and enforce a rigorous CI/CD and GitOps-based discipline. You will be responsible for building the automated pipelines that enable our "relentless shipping" culture, allowing us to deploy to production safely and multiple times a day.
• Unify the Data Layer: Design and manage our central data lakehouse (e.g., Databricks, Snowflake) to act as the "single source of truth," serving real-time analytics for our SaaS platform and batch workloads for AI research.

Ideal Candidate Profile

• A "Full-Stack" Infrastructure Engineer: You are a systems-level thinker who is equally comfortable in the domains of cloud-native infrastructure (K8s, Networking), data engineering (Kafka, Spark), and MLOps (GPU workloads, orchestration).
• Deep Cloud-Native Expertise: You have multiple years of hands-on, in-production experience with Kubernetes, Terraform (or other IaC), and a major cloud provider (AWS/GCP/Azure).
• CI/CD & Automation Fanatic: You live and breathe automation. You have extensive experience building and maintaining robust CI/CD pipelines (e.g., GitLab CI, Jenkins, ArgoCD) and believe GitOps is the standard.
• SaaS & MLOps Fluency: You have ideally built platforms that serve both external B2B customers (with SLAs, security, and multi-tenancy) and internal R&D teams (with needs for flexibility, speed, and massive compute).
• A "Relentless Shipper" (Startup Mentality): You are a pragmatic, proactive builder who thrives in a fast-paced startup environment. You understand that "done" is better than "perfect" and are comfortable with tight release schedules and high ownership.
• Technical Polyglot: You possess deep expertise in Python and/or Go, shell scripting, and the modern data stack (SQL, orchestration tools, streaming platforms).