Summary

We are seeking a highly skilled and motivated AI Application Development Engineer to join our innovative team. The ideal candidate will have expertise in designing, developing, and deploying AI-driven applications, with a strong foundation in machine learning (ML), deep learning (DL), and Large Language Models (LLMs). Proficiency in Python, SQL, and cloud technologies, along with an interest in finance and blockchain, is highly desirable.

The role requires hands-on experience with LLM-based AI application development, Retrieval-Augmented Generation (RAG), AI agents, and prompt engineering to optimize large model performance. The candidate will work closely with cross-functional teams to build AI-driven solutions that enhance business operations and decision-making.

Key Responsibilities

1. Develop and deploy AI-powered applications utilizing LLMs, machine learning, and deep learning techniques.
2. Design and optimize AI-driven agents for various business and automation use cases.
3. Implement and enhance Retrieval-Augmented Generation (RAG) systems for efficient information retrieval and knowledge-based AI solutions.
4. Utilize prompt engineering techniques to fine-tune LLM responses and improve model effectiveness.
5. Extract, process, and analyze large-scale datasets to drive AI insights and business intelligence.
6. Integrate AI models into production systems, ensuring scalability, performance, and reliability.
7. Collaborate with data scientists, engineers, and business teams to align AI applications with organizational goals.

Requirements

1. Education:
2. Master’s degree or higher in Computer Science, Artificial Intelligence, Data Science, or a related field.
3. Technical Skills:
4. Proficiency in Python, SQL, and PySpark for AI model development and data processing.
5. Strong foundation in ML/DL algorithms, including SVM, LSTM, CNN, Transformers (e.g., BERT, GPT).
6. Hands-on experience with Large Language Models (LLMs) and applications such as RAG, Knowledge Graph RAG, and AI Agents.
7. Expertise in fine-tuning, pretraining, and optimizing LLMs for AI-driven applications.
8. Experience with deep learning frameworks such as PyTorch or TensorFlow.
9. Familiarity with cloud platforms (AWS, GCP, Azure) and deployment of AI models in a cloud environment.
10. Experience with AI-driven application frameworks for integrating models into real-world business use cases.
11. Knowledge of data analytics platforms (e.g., Databricks) is a plus.
12. Soft Skills:
13. Strong problem-solving and analytical thinking abilities.
14. Excellent communication and collaboration skills.
15. Ability to work independently and manage multiple AI projects effectively.

Skills

• Analytical Thinking
• App Development
• AWS
• Database Management
• Development
• Python
• Software Engineering
• SQL