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

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.