Machine Learning Engineer - AI Agent Platform
- Compensation
- Not disclosed
- Location
- Singapore
- Work setup
- Onsite
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- 5+ years
- Category
- Ml / AI
- Posted
Skills
Must have
- 5+ years of professional software development experience, including delivery of production applications across backend and frontend.
- Strong Python skills with FastAPI or similar frameworks, asynchronous programming, REST APIs, SQLAlchemy/Pydantic or equivalent tooling, and PostgreSQL data modeling.
- Hands-on experience with LLM tool calling, agent execution, or workflow orchestration; practical examples explaining design decisions, context and state management, and failure handling.
- Experience integrating enterprise or third-party systems, including API contracts, data mapping, pagination, rate limits, and retries.
- Understanding of OAuth 2.0/OIDC, authorization, role-based access control, and secure credential handling in applications.
- Ability to build reliable asynchronous workflows using task state, concurrency control, idempotency, and recovery from partial failures.
- Proficiency in TypeScript and Vue or React, including routing, state management, and reusable components. Vue 3 is preferred; willingness to adapt is essential.
- Experience with automated and integration testing, Git, CI/CD, and Docker; ability to troubleshoot using logs and metrics and evaluate agents against representative tasks.
- Clear communication with global, cross-functional teams and the ability to explain technical tradeoffs to non-technical stakeholders.
Nice to have
- Experience extending agent harnesses, SDKs, or orchestration frameworks such as LangGraph, LangChain, or custom implementations.
- Development of MCP servers, connectors, plugins, or SDKs; integrations with Microsoft Graph, Teams, SharePoint, Jira, ERP, or similar systems.
- Experience with long-running workflows, human approval, durable task state, recovery, or agent evaluation frameworks.
- Hands-on cloud deployment and operations experience, preferably AWS; familiarity with caching, queues, NoSQL databases, or vector search.
- Electron development or plugins for desktop and productivity applications.
Full description
PLAY, GROW and WIN
To be a part of Virtuos means to be a creator.
At Virtuos, we harness the latest technologies to make games better and more immersive than ever before. That is why we pride ourselves in constantly pushing the boundaries of possibility since our founding in 2004.
Virtuosi is a team of experts - people who have come together to share their mutual passion for making and playing games. People with the same enthusiasm for exploring new ideas and the constant drive to excel in their field. People who believe in earning success through dedication.
At Virtuos, we are at the forefront of gaming, creating exciting new experiences daily. Join us to Play, Grow and Win - together.
ABOUT THE POSITION
We are looking for a hands-on Machine Learning Engineer to develop an enterprise AI agent platform, with a strong backend focus. You will build agent execution and orchestration capabilities, integrate enterprise systems, and deliver secure, reliable features from backend services to frontend interfaces
RESPONSIBILITIES
- Agent platform and orchestration
- Build and improve agent harnesses, including model and tool execution loops, context management, and structured outputs.
- Implement multi-step workflows with clear execution boundaries, task state, asynchronous dispatch, and human approval where needed.
- Enterprise systems and integrations
- Develop reusable tools and connectors for enterprise APIs, webhooks, and services, with clear input and output contracts.
- Handle data mapping, user authorization, rate limits, and integration errors; document dependencies with system owners.
- Full-stack product delivery
- Design Python backend services, secure REST APIs, and PostgreSQL data models for agent and workflow features.
- Build responsive web interfaces for task progress, user confirmations, and results using TypeScript and modern frontend frameworks.
- Security and reliability
- Protect credentials, preserve user access boundaries across systems, and apply appropriate execution isolation and audit logging.
- Improve concurrency control, retries, idempotency, cancellation, and recovery; trace failures across model calls, tools, and workers.
- Quality and collaboration
- Maintain automated and integration tests, CI/CD, and agent evaluations covering task success, output quality, latency, and cost.
- Work with product, design, IT, SRE, and business system owners; contribute code reviews, documentation, and technical guidance.