[Hiring] Full-Stack AI Engineer @Inficare Technologies

Role Description

We are seeking a mid-level Full-Stack AI Engineer to join a fully remote, globally distributed engineering team. In this role, you will design, build, and ship ML and AI systems in production - with a focus on LLM-based applications, retrieval-augmented generation (RAG), and modern AI coding practices. You'll work across the full stack of AI engineering, from model integration to deployment on cloud infrastructure.

Key Responsibilities

• Build and ship production ML/AI systems leveraging large language models and AI coding tools
• Design and implement RAG pipelines and embedding-based solutions using production vector stores
• Deploy and operate services on Azure (AKS, App Service, Functions, Azure AI/ML) using containerization (Docker)
• Build and maintain CI/CD pipelines (Azure DevOps, GitHub Actions) for production workloads
• Contribute to code reviews using Git and pull-request-based workflows
• Communicate modeling decisions and trade-offs clearly to non-technical stakeholders

Qualifications

• Python, PyTorch and/or TensorFlow, scikit-learn, pandas, NumPy
• LLM deployment - Anthropic Claude, Azure OpenAI, OpenAI, or open-source models
• RAG, embeddings, and vector store experience (at least one production deployment)
• AI coding tools - Claude Code, Cursor - balanced with strong manual coding fundamentals
• Git, branching strategies, pull-request-based code review
• CI/CD pipelines - Azure DevOps, GitHub Actions
• Azure cloud services - AKS, App Service, Functions, Azure AI/ML; Docker containerization

Preferred Skills

• Experience in globally distributed, fully remote engineering environments
• Strong written and verbal communication skills for cross-functional collaboration

Location & Work Model

Fully Remote - candidates must be comfortable working in a globally distributed team environment.

Engagement Details

Mid-level position. Contract engagement. Bachelor's or Master's degree in Computer Science, Machine Learning, Data Science, Mathematics, Statistics, or a related field - or equivalent practical experience required.