The Software Engineer - AI Systems role offers an opportunity to develop proactive digital assistants that combine artificial intelligence (AI) reasoning, long-term context, and automation to help users complete everyday tasks with less manual effort. As part of a broader recruitment initiative across several engineering functions, the role's day-to-day responsibilities may vary according to team placement and seniority. It requires a strong foundation in modern software engineering, AI systems, backend development, machine learning, and production infrastructure, supported by a technology stack shared across the engineering teams.

Responsibilities

AI Product Development

Design, build, and deploy AI-powered product features
Integrate large language models, memory systems, vector databases, and external tools into production applications
Design agent workflows capable of planning, tool usage, failure handling, and recovery
Transform raw model outputs into structured, reliable, and predictable user experiences

Backend & Platform Engineering

Build and maintain backend services, application programming interfaces, and orchestration layers supporting AI features
Develop scalable inference pipelines and service architectures
Optimise latency, throughput, caching, batching, and streaming workloads
Design robust monitoring, logging, alerting, and observability systems

Machine Learning & Applied AI

Train, evaluate, fine-tune, and deploy machine learning models
Develop evaluation frameworks to measure model and system performance
Improve model reliability, accuracy, and production effectiveness through continuous iteration
Debug model failures and production issues using real-world data and feedback

Production Operations

Ensure the reliability, scalability, and availability of AI systems in production
Build fallback and recovery mechanisms for model and tool failures
Monitor system health, troubleshoot incidents, and improve operational excellence
Balance performance, cost, security, and user experience

Cross-functional Collaboration

Work closely with Product, Engineering, and AI teams to translate ambiguous requirements into working solutions
Contribute to technical decision-making, architecture reviews, and engineering best practices
Mentor team members and promote high engineering standards where appropriate

Requirements

Bachelor's degree in Computer Science, Artificial Intelligence, Machine Learning, Software Engineering, or a related field
Minimum 3 years of experience in software engineering, backend engineering, machine learning engineering, applied AI, or a related technical role
Strong programming skills in Python
Experience building and deploying production systems
Understanding of application programming interface design, distributed systems, and system architecture
Experience working with SQL and/or NoSQL databases
Familiarity with Docker, Kubernetes, and cloud-native environments

Technology stack

Languages

Python
Node.js

AI & Machine Learning

OpenAI
Anthropic
Open-source large language models
PyTorch
JAX
Vector databases

Backend & Infrastructure

SQL/NoSQL
Docker
Kubernetes
AI inference platforms, including vLLM and related serving technologies

Frontend

Next.js

About the company

An innovative AI financial technology (fintech) company developing proactive digital assistants that go beyond responding to prompts. By combining AI reasoning, long-term context, and automation, the organisation aims to help users complete everyday tasks faster, more efficiently, and with less manual effort.

JAC Recruitment Pte. Ltd.
EA Licence: 90C3026
EA Personnel Name: Syahirah Binte Ahmad Ja'afar
EA Personnel: R22105331

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