NLP AI Engineer for Multilingual Localization and RAG

Localizationacademy; Livonia (MI); Hybrid; USD 90,000 - 162,000; Full time

Job summary

Siemens Software is seeking a software developer to advance localization efforts with AI-driven applications and data workflows. You will design, code, and optimize AI agents, translation workflows, and language models, collaborating with cross-functional teams to deliver integrated localization solutions.

The role emphasizes advanced NLP/ML techniques, RAG data retrieval, and continuous improvement of AI capabilities across cloud platforms and enterprise systems.

Qualifications

• Bachelor's degree in CS, Data Science, Computational Linguistics, AI, or related field.
• 3+ years of professional experience developing applications and solutions, cloud-hosted or connected.
• Experience multilingual projects and AI/RAG systems.
• Experience building vector databases for efficient retrieval.
• Experience embedding models for document processing and chunking strategies.

Responsibilities

• Develop, evaluate, deploy and document AI capabilities, applications and solutions.
• Design and build AI agents, chatbots, and web apps.
• Optimize localization data workflows and glossary/terminology management.
• Collaborate with cross-functional teams to integrate AI into products.
• Stay updated on NLP and ML advancements and apply to localization workflows.

Skills

C++

Java

Python

Cloud platforms

Gen AI / LLMs

Vector DBs

MLOps / CI-CD

NLP / NLG

Prompt engineering

Cross-functional teamwork

Education

Bachelor's degree in CS / Data Science / Computational Linguistics / AI

Master's degree (plus)

Tools

AWS

Azure

Google Cloud

Job description

Siemens Software is seeking a software developer to advance localization efforts with AI-driven applications and data workflows. You will design, code, and optimize AI agents, translation workflows, and language models, collaborating with cross-functional teams to deliver integrated localization solutions.

The role emphasizes advanced NLP/ML techniques, RAG data retrieval, and continuous improvement of AI capabilities across cloud platforms and enterprise systems.