AI Engineer (LLM / NLP, Production Systems)

AI Engineer (NLP / Production AI, Aviation Domain)

Itexus is looking for a Senior AI Engineer to join a long-term project for a US-based client in the aviation domain.

The product focuses on improving operational efficiency by working with large volumes of technical data, documentation, and system-generated information. It is a cloud-based, AI-driven platform that provides analytics and insights to support decision-making.

This role focuses on building and integrating production-ready AI solutions, with a strong emphasis on NLP, modern models, and real-world data.

About the Role

You will work on integrating AI into a production system operating in a complex, data-rich environment. The role requires hands-on experience with deploying AI solutions and working with unstructured data such as documents, logs, and telemetry.

This is a practical engineering role focused on building, deploying, and scaling AI systems within real-world applications.

Key Responsibilities

• Design and implement AI-powered features for a production platform
• Work with NLP and modern AI models (including LLMs and embeddings)
• Process and analyze unstructured data (technical documents, logs, telemetry)
• Build data pipelines and integrate AI solutions into backend systems
• Develop and deploy scalable AI services
• Work on tasks such as data clustering and anomaly detection
• Collaborate with engineers and product teams to deliver reliable solutions

Requirements

• 4+ years of experience in AI / ML / Software Engineering
• Strong Python skills
• Proven experience deploying AI/ML solutions into production
• Strong background in NLP (text processing, semantic search, clustering, etc.)
• Hands-on experience with LLMs and modern AI models
• Experience with data mining and data engineering
• Experience working with real-world datasets (documents, logs, telemetry)
• Understanding of building scalable systems and integrating APIs
• English level B2 or higher

Nice to Have

• Experience with MLOps (deployment, monitoring, model lifecycle)
• Experience with vector databases and semantic search systems
• Background in anomaly detection and statistical modeling
• Experience with distributed systems and microservices architecture
• Experience with speech/voice processing

We’ll be happy to tell you more about the project, team, and company during the interview process.