🛠 Tech Stack

💼 About This Role

You'll bridge the gap between theoretical AI research and practical business applications, building end-to-end LLM-powered features and optimizing retrieval-augmented generation (RAG) pipelines. You'll ensure the reliability of AI services in a cloud-native environment.

🎯 What You'll Do

• Design and deliver production applications using LLM APIs and orchestration frameworks.
• Build and optimize retrieval systems with vector databases and hybrid search.
• Develop autonomous agents and multi-step reasoning workflows.
• Establish evaluation pipelines to measure model drift, accuracy, and latency.
• Package AI applications in Docker and manage cloud deployments with CI/CD.

📋 Requirements

• Bachelor’s or Master’s degree in Computer Science, AI, or related field.
• Expert-level proficiency in Python (3.10+).
• Strong understanding of machine learning, deep learning architectures (Transformers), and NLP fundamentals.
• Hands-on experience with Docker, Kubernetes, and cloud-native AI tools.
• Proficiency in SQL and experience with Vector Databases.

✨ Nice to Have

• Experience fine-tuning open-source models like Llama 3 or Mistral.
• Knowledge of AI ethics, bias mitigation, and responsible AI governance.
• Relevant certifications (e.g., Azure AI Engineer Associate).

🎁 Benefits & Perks

• 🏖️ Remote work
• 🏥 Health insurance
• 💻 Cutting-edge tech stack
• 🌍 Global team collaboration
• 📚 Learning opportunities

📨 Hiring Process

Estimated timeline: 2-4 weeks · AI estimate

1. 1Recruiter Call· 30 min
2. 2Technical Interview· 60 min
3. 3Final Interview· 60 min