Jobtitel: AI Engineer - energy industry
Zahlungsintervall: Stündlich
Lohnsatz: Verhandelbar
Ort: CZ
Job veröffentlicht: 28-05-2026
Job-ID: 75539
Name: Shweta Patil
Telefonnummer: +494085537032
E-Mail: Shweta.Patil@nemensis.de

Stellenbeschreibung

AI Engineer - energy industry


Start: asap
Duration: 6 months (option of extension)
Location: remote
Language: English
EU only


Key Requirements

Must-have
• Data engineering pipelines (preprocessing, ingestion, transformation)
• LLMs / AI systems in production
• Strong programming skills (Python expected)
• APIs (e.g. FastAPI)
• Handling unstructured data (PDFs, OCR, images)
• Multi-modal AI (text + image)
• Real-time / low-latency systems
• Cloud & infrastructure (Terraform)
• CRM integrations


Understanding of:
• Data quality, validation & monitoring
• Security / filtering layers in AI systems

 

Project Description – AI-Driven Customer Enablement Platform

Building an AI-driven, LLM-based platform to support customer service teams in handling incoming 
customer interactions (emails, letters, documented calls). The goal is to create a centralized AI system 
that enriches and leverages a 360° customer data view to improve efficiency, routing, and decisionmaking. The platform integrates with an existing Microsoft CRM system and builds on current workflows. 
The focus is on establishing scalable data foundations and reusable AI capabilities for multiple future 
use cases.
-Highly cross-functional environment with overlapping responsibilities


Responsibilities
• Design & implement data pipelines and preprocessing workflows
• Work with LLMs in production environments
Contribute to:
• Prompt engineering
• Model orchestration
• Evaluation & quality assurance
• Support multi-modal processing (text, PDFs, images)
• Integrate AI components into existing systems & APIs
• Infrastructure as Code (Terraform)
• Service architecture


Expectations
• Strong AI Engineering mindset, but hands-on with data
• Comfortable working across different areas (AI, data, backend)
• Flexible and pragmatic ("not just LLM modeling")
• Able to work in early-stage, evolving environment