Lead Full-Stack Engineer: Gen AI Platforms & Systems

Capgemini; Singapore; On-site; SGD 180,000 - 260,000; Full time

Benefits offered by this job

Flexible work practices

40 hours of self-development per year

Job summary

Capgemini Singapore is seeking an Architect to lead an agile, cross-functional team delivering AI-powered search and systems. You will design scalable, secure architectures, balance performance, cost and security, and guide the team from experimentation to production-ready solutions.

You will architect and implement LLM integrations, RAG workflows and vector search while promoting DevOps, TDD, and responsible AI practices across projects with product and design partners.

Qualifications

• 5-7+ years of experience in web application development.
• Proven experience leading agile development teams.
• Strong hands-on experience with Node.js, TypeScript, Cloud platforms (Azure, AWS, GCP).
• Experience with SQL & NoSQL databases and CI/CD pipelines.
• Production experience integrating LLMs into applications.
• Understanding of AI governance, security, and responsible AI practices.

Responsibilities

• Provide technical leadership to an agile, cross-functional development team.
• Define and communicate technical vision across multiple workstreams.
• Design scalable, secure architectures for AI-powered systems.
• Lead DevOps adoption including build, release automation, and infrastructure improvements.
• Oversee automated testing strategy (unit, integration, performance).
• Mentor and coach engineers to grow technically and professionally.
• Collaborate with Product Owners and UX Designers for feasibility and estimation.

Skills

Node.js

TypeScript

Cloud platforms

SQL & NoSQL

CI/CD

DevOps

Search engines

Semantic search

RAG architectures

LLM integration

AI governance

Stakeholder management

Mentoring

Job description

Capgemini Singapore is seeking an Architect to lead an agile, cross-functional team delivering AI-powered search and systems. You will design scalable, secure architectures, balance performance, cost and security, and guide the team from experimentation to production-ready solutions.

You will architect and implement LLM integrations, RAG workflows and vector search while promoting DevOps, TDD, and responsible AI practices across projects with product and design partners.