Lead AI Software Engineer with 7 year Experience (Contract - D14 Geylang, Eunos, SG

Roles & Responsibilities

[1 year contract, renewable]

About the Role

We are seeking a Lead Software Engineer with deep expertise in full stack development , Generative AI , and DevSecOps practices . This is a hands-on leadership role at the forefront of building AI-native products that combine robust engineering with cutting-edge generative capabilities.

You will drive the architecture, development, and deployment of secure, scalable applications infused with AI — from LLM-powered experiences and intelligent agents to automated workflows and decisioning systems . Beyond technical execution, you will embed shift-left quality and security , mentor engineers, and set the direction for how Generative AI shapes our product strategy.

Key Responsibilities

• Generative AI Engineering
• Design and build LLM-powered applications (retrieval-augmented generation, multi-agent systems, generative search, AI copilots).
• Implement prompt engineering, fine-tuning, and evaluation frameworks for production-grade reliability.
• Optimize AI inference at scale (latency, cost efficiency, guardrails).
• Ensure responsible AI use (bias detection, explainability, data privacy).
• Full Stack Development
• Architect and deliver end-to-end features across frontend (React / Next.js) , backend (Node.js / Python / Java) , and cloud-native infrastructure .
• Build secure APIs, data pipelines, and real-time services that power AI-driven user experiences.
• DevSecOps & Shift-Left Practices
• Embed security and testing early in the development lifecycle.
• Own CI / CD pipelines with automated testing, vulnerability scanning, and compliance guardrails.
• Implement Infrastructure as Code (IaC) and observability for resilience and scalability.
• Leadership & Collaboration
• Mentor engineers on AI software engineering best practices.
• Collaborate with product managers and data scientists to translate business problems into AI-first solutions.
• Drive technical decision-making, balancing innovation speed with long-term system sustainability.

Qualifications

Must-Have :

o LLM integration (OpenAI, Anthropic, Llama, etc.)

o RAG pipelines (vector databases, embeddings, semantic search)

o Fine-tuning and evaluation of models

o Safety / guardrail implementation

Nice-to-Have :

Tell employers what skills you have

Security Clearance

Generative model

Sustainability

Leadership

Scalability

Vulnerability Scanning

Kubernetes

Azure

Pipelines

Architect

Software Engineering

Reliability

Distributed Systems

Engineering Design

Docker

GCP

Orchestration