AI Platform Engineer

SCHONFELD STRATEGIC ADVISORS (SINGAPORE) PTE. LTD.; Singapore; On-site; SGD 110,000 - 180,000; Full time

Job summary

Schonfeld Strategic Advisors (Singapore) PTE. LTD. is seeking a Platform Engineer to join the AI Technology team. You’ll ensure stability and scalability of the internal Agentic AI platform, contribute code and automation, and support users through incidents while driving observability and best practices.

The role focuses on reliability, incident response, and scalable architecture, working in a fast-paced environment with evolving requirements and strong stakeholder engagement.

Qualifications

• 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 creating and integrating REST APIs, and event-driven and asynchronous architectures.
• Experience with relational databases (Postgres, MySQL) and NoSQL databases (DynamoDB, Elastic Search).
• Experience with AWS services (S3, OpenSearch, DynamoDB), Kubernetes-driven deployments, Github Actions, and modern CI/CD pipelines.
• A passion for AI and ways it can solve problems and boost productivity.
• Ability to break down complex issues methodically.
• Excellent communication skills; able to translate technical concepts for non-technical stakeholders.

Responsibilities

• Set reliability standards for Enterprise AI, defining SLOs, error budgets, and incident runbooks.
• Own observability, incident response, reliability, and scalability of the AI platform.
• Ensure agents, gateways, LLM proxies, and RAG pipelines operate with high availability and cost efficiency.
• Support users via a dedicated help channel, investigate root causes, and communicate updates.
• Contribute to code quality and best practices, identify gaps in development lifecycles, and continuously improve the platform and developer experience.

Skills

Python

REST APIs

Async architectures

AWS

Kubernetes

CI/CD

Observability

SRE

Communication

Tools

DataDog

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