AI Platform Engineer — Remote-Ready LLM SaaS

DiliTrust; Paris; Hybrid; EUR 75,000 - 120,000; Full time

Benefits offered by this job

Lunch vouchers

Profit sharing

CSE benefits

Job summary

DiliTrust is seeking a Software Engineer to join the AI Platform squad in Paris. You will work at the intersection of AI, product, and engineering to build, improve, and scale Lini-powered features across the DiliTrust suite.

You will collaborate with ML, product, and engineering teams, contribute to architecture decisions for LLM integration and scalability, and uphold engineering standards including testing, observability, and CI/CD.

Qualifications

• 5+ years of professional software engineering experience on B2B SaaS platforms.
• End-to-end ownership from scoping to deployment and iteration.
• Experience working in cross-functional teams (product, design, ML, data).
• First exposure to AI/ML-powered products is a strong plus.

Responsibilities

• Design, build, and maintain Lini-powered features across the DiliTrust suite from API design to frontend integration.
• Collaborate with ML, Product Managers, and other engineering squads to ship high-quality AI features.
• Contribute to architecture discussions on LLM integration, context management, and scalability.
• Write well-tested, documented, maintainable code; participate in code reviews.
• Help define and uphold the squad's engineering standards: testing, observability, CI/CD.
• Identify cross-team dependencies early and help unblock them.
• Continuously improve understanding of LLM patterns and AI product design.

Skills

Ownership

Clear communication

Product mindset

Collaborative

Stakeholder in squad outcomes

Tools

Vue.js 3

Node.js

TypeScript

REST APIs

Docker

Kubernetes

Terraform

PostgreSQL

MariaDB

GCP

Job description

DiliTrust is seeking a Software Engineer to join the AI Platform squad in Paris. You will work at the intersection of AI, product, and engineering to build, improve, and scale Lini-powered features across the DiliTrust suite.

You will collaborate with ML, product, and engineering teams, contribute to architecture decisions for LLM integration and scalability, and uphold engineering standards including testing, observability, and CI/CD.