Forward Deployed Engineer

EDULEAD INVESTMENTS PTE. LTD.; Singapore; On-site; SGD 90,000 - 150,000; Full time

Job summary

EDULEAD INVESTMENTS PTE. LTD. in Singapore is seeking an engineer to architect and develop production AI/agentic systems, manage the product roadmap, and rapidly test and evaluate systems for real-world business use.

You will continuously interface with clients to co-design AI and security best practices, translating complex concepts into actionable plans. The role requires 2–3+ years in AI, strong Python skills, and proven system design maturity, with exposure to MCPs, RAG, and cloud tooling.

Qualifications

• BS or MS in Computer Science or closely-related field.
• 2 to 3+ years of relevant industry experience or equivalent.
• Direct experience shipping an AI or agentic AI system end-to-end to users, preferably owned or led the project.
• Excellent communication skills, particularly in communicating technical concepts in an approachable way to clients.
• Proficiency in Python.
• Strong production maturity and system design skills.
• Familiarity with agentic tooling and development, including Model Context Protocols (MCPs), agent skills, agent orchestration, Retrieval Augmented Generation (RAG), etc.
• Experience designing evals, observability and monitoring for AI, plus debugging failure modes in production.
• Knowledge of enterprise security best practices to securely deploy AI and software.
• Proficiency in building data pipelines and API integrations.
• Familiarity with cloud platform (AWS (preferred)/Azure/GCP), infrastructure as code, containerization.
• Passion for experimenting with AI models, open-source repos, etc.
• Knowledge of latest developments in AI capabilities and deployment strategies.

Responsibilities

• Architect and develop production AI / agentic systems for business use, including agent infrastructure and client integrations.
• Manage AI product development roadmap.
• Rapid testing and evaluation of agentic systems, including reliability engineering, performance measurement and cost management.
• Continuously interface with clients to understand areas for transformation and co-design AI and security best practices.

Skills

Python

Communication skills

System design

AI knowledge

Cloud platforms

Data pipelines

API integrations

MCPs

Education

BS/MS in Computer Science

Tools

AWS

Azure

GCP

Docker

Kubernetes

Terraform

Job description

Join Us. Grow With Us. Shape What’s Next.
We are looking for passionate, creative and forward-thinking engineer to join our new start up!

Main Responsibilities:

• Architect and develop production AI / agentic systems optimized for business use cases, including agent infrastructure and integrations with client infrastructure

• Manage AI product development roadmap

• Rapid testing and evaluation of agentic systems, including reliability engineering, performance measurement and cost management

• Continuously interface with clients to understand areas for transformation and co-design AI and security best practices

Required experience and qualifications:

• BS or MS in Computer Science or closely-related field

• 2 to 3+ years of relevant industry experience or equivalent

• Direct experience shipping an AI or agentic AI system end-to-end to users, preferably owned or led the project

• Excellent communication skills, particularly in communicating technical concepts in an approachable way to clients

• Proficiency in Python

• Strong production maturity and system design skills

• Familiarity with agentic tooling and development, including Model Context Protocols (MCPs), agent skills, agent orchestration, Retrieval Augmented Generation (RAG), etc.

• Experience designing evals, observability and monitoring for AI, plus debugging failure modes in production

• Knowledge of enterprise security best practices to securely deploy AI and software

• Proficiency in building data pipelines and API integrations

• Familiarity with cloud platform (AWS (preferred)/Azure/GCP), infrastructure as code, containerization

• Passion for experimenting with AI models, open-source repos, etc.

• Knowledge of latest developments in AI capabilities and deployment strategies

Good to haves

• Experience deploying AI in a specific vertical or business use case

• Ability to identify and articulate business value from AI deployments — including ROI framing, process mapping, and stakeholder alignment

• Familiarity with enterprise software ecosystems, including Oracle SAP, Microsoft, etc.

• Proficiency in additional languages such as TypeScript, SQL, Java, Go

• Familiarity with data privacy practices for AI

• Experience with on-device or on-prem data management or AI deployment.

• Familiarity with ML frameworks such as PyTorch, TensorFlow, etc.