Mid-Level AI Engineer (Gen AI / LLMs) - Remote Opportunity

Posted 3 Hours Ago
Be an Early Applicant
Hiring Remotely in Geneva, CHE
In-Office or Remote
Mid level
Information Technology • Software
The Role
Develop and deploy production-ready Generative AI applications using LLMs and RAG. Integrate OpenAI/AWS Bedrock APIs into systems, collaborate with data engineering, tune performance, monitor deployments, and document solutions for technical and non-technical stakeholders.
Summary Generated by Built In

We are looking for a remote Mid-Level AI Engineer with hands-on experience building and deploying Generative AI solutions.

This is an engineering role focused on developing production-ready applications using Large Language Models (LLMs), RAG, and cloud AI platforms such as AWS Bedrock or OpenAI APIs. This is not a research-focused position.

Before you apply, please ensure you meet the following minimum requirements:

  • Professional experience developing applications in Python.
  • Hands-on experience building or deploying LLM-based applications.
  • Experience with RAG, OpenAI/AWS Bedrock APIs, or similar GenAI frameworks.
  • Experience integrating AI solutions into production or business applications.
  • Strong English communication skills.

Key Accountabilities

  • Model Customization & RAG: Implement retrieval-augmented generation techniques to customize LLMs for practical business use.
  • API & Platform Integration: Use AWS Bedrock, OpenAI or similar APIs to embed generative AI into existing systems.
  • Applied Solution Development: Build AI-powered tools to enhance operational efficiency, decision-support systems, or customer workflows in industry settings.
  • Data Prep & Collaboration: Work with data engineering to preprocess and manage data for model inputs, ensuring security and compliance.
  • Performance Tuning & Production Deployment: Monitor and refine LLM deployments in scalable, reliable environments.
  • Cross-Functional Partnership: Collaborate with software engineers, product managers, and stakeholders to deliver AI solutions that meet real needs.
  • Documentation & Communication: Create clear documentation and explain technical concepts to both technical and non-technical audiences in a hands-on context.

Qualifications Minimum Qualifications

  • Background: 1–3 years (or more) of applied experience in Software, Data, or ML Engineering (e.g., backend, data pipelines, model implementation).
  • Technical Fluency: Strong Python skills and experience with ML frameworks (TensorFlow, PyTorch, scikit-learn).
  • Cloud Experience: Familiarity with AWS, GCP, or Azure integration.
  • Generative AI Passion: Interest in LLMs, prompt engineering, RAG, and applied AI, demonstrated through project work or prior deployments.
  • Problem-Solving & Ownership: Ability to take a project from prototype to delivery, optimizing for performance and business value.
  • Soft Skills: Clear communication, cross-functional collaboration, agile mindset.
  • Education: Bachelor’s or Master’s in Computer Science, Engineering, Data Science, PhD not required.

Pluses (Nice to Have)

  • Experience with LLM fine-tuning, prompt engineering, or LangChain/Agent frameworks.
  • Familiarity with MLOps tools (e.g., MLflow, Docker, CI/CD pipelines).
  • Industry-specific experience (e.g. maritime, logistics, finance) is a bonus, but we prioritize applied engineering experience over domain knowledge.

We are looking forward to your application.

Skills Required

  • Professional experience developing applications in Python.
  • Hands-on experience building or deploying LLM-based applications.
  • Experience with RAG and OpenAI/AWS Bedrock APIs or similar GenAI frameworks.
  • Experience integrating AI solutions into production or business applications.
  • Strong English communication skills.
  • 1-3 years applied experience in Software, Data, or ML Engineering.
  • Experience with ML frameworks (TensorFlow, PyTorch, scikit-learn).
  • Familiarity with cloud integration (AWS, GCP, or Azure).
  • Ability to take a project from prototype to delivery, optimizing for performance and business value.
  • Clear communication, cross-functional collaboration, and agile mindset.
  • Bachelor's or Master's degree in Computer Science, Engineering, or Data Science.
  • Experience monitoring, refining, and deploying LLMs in scalable, reliable environments.
  • Experience with LLM fine-tuning, prompt engineering, or LangChain/Agent frameworks.
  • Familiarity with MLOps tools (MLflow, Docker, CI/CD pipelines).
  • Industry-specific experience (maritime, logistics, finance) as a bonus.
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The Company
HQ: Geneva, Geneva
40 Employees
Year Founded: 2010

What We Do

Umanova provides paramount customisation to reduce the costs of IT Services and Solutions; creating new and profitable ventures.

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