AI Platform Engineer

SCHONFELD STRATEGIC ADVISORS (SINGAPORE) PTE. LTD.; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

SCHONFELD STRATEGIC ADVISORS (SINGAPORE) PTE. LTD. is seeking a Platform Engineer to join its AI Technology team.

You will help scale and stabilize the internal Agentic AI platform, contribute code, automation, and observability, and support users in a fast-paced environment. You will define reliability standards, own SLOs and incident response, and work across agents, gateways, LLM proxies, and RAG pipelines to ensure high availability and performance.

Qualifications

• 5+ years in cloud automation or site reliability engineering.
• Experience developing Python applications.
• Experience designing REST APIs and asynchronous architectures.
• Proficient with relational and NoSQL databases (PostgreSQL/MySQL, DynamoDB/Elasticsearch).
• Familiar with AWS services and Kubernetes deployments; strong CI/CD practice.

Responsibilities

• Set reliability standards: define SLOs, error budgets and incident response runbooks.
• Own observability, incident response, reliability and scalability of the AI platform.
• Ensure agents, gateways, LLM proxies and RAG pipelines are highly available and efficient.
• Support users via dedicated help channel; diagnose root causes and communicate updates.
• Contribute to code quality and lifecycle improvements across the platform.

Skills

Python

SRE/Platform engineering

REST APIs

Asynchronous architectures

AWS

Kubernetes

CI/CD pipelines

Observability

Tools

GitHub Actions

DataDog

OpenSearch

Job description

The Role

We’re looking for a Platform Engineer to join our AI Technology team and play a critical role in ensuring the stability and scalability of the firm’s internal Agentic AI platform. This is a high-impact, hands‑on engineering position where you’ll contribute code, automation workflows, observability, metrics, and support users as issues arise. You’ll work in a dynamic, fast‑paced environment where product requirements evolve, and business stakeholders are deeply engaged.

What you’ll do

• You will set the reliability standards for Enterprise AI, defining Service Level Objectives (SLOs), error budgets, and custom incident response runbooks.
• You will own the observability, incident response, reliability, and scalability of our AI platform.
• Ensure that our agents, gateways, LLM proxies, and RAG pipelines operate with high availability, accuracy, and financial efficiency.
• Support users in a dedicated help channel when issues arise — investigating root causes, providing solutions, monitoring the status of upstream dependencies, and communicating updates back to users.
• You’ll also be involved in the team’s code quality and best practices, identify gaps in development lifecycles, and continuously improve both the core platform and how developers build with it.

What you need:

• 5+ years of professional cloud automation or site reliability engineering experience, or similar
• Familiarity with software development best practices and experience creating applications in Python
• Experience working creating and integrating REST APIs, and event‑driven and asynchronous architectures
• Experience working with both relational (Postgres, MySQL) and NoSQL databases (DynamoDB, Elastic Search)
• Experience with AWS cloud services (S3, OpenSearch, DynamoDB, etc.), Kubernetes‑driven deployments, Github Actions, and modern CI/CD pipelines
• A passion for AI, creative ideas for how it can be a tool for problem solving and productivity
• A thoughtful approach to problem‑solving; ability to break down complex issues methodically
• Excellent communication skills; Able to translate technical concepts for non‑technical stakeholders

We’d love if you had:

• Experience developing agentic AI applications, harnesses, MCP servers, and workflows
• Familiarity with or experience building AI agents, Retrieval‑Augmented Generation (RAG) pipelines, or agentic tools
• Experience with observability tooling such as DataDog