AI engineer with Python experience developing applications powered by LLMs and integrating with data warehouse like GCP Big Query & other standard data sources.

Required Skills and Qualifications:

3+ years of proven experience in Python software development (Full stack or Backend), with a strong emphasis on backend development. Strong knowledge on Python data structures and algorithms Proficiency with Python and relevant libraries such as Pandas, NumPy, SciPy, scikit-learn, PyTorch, TensorFlow, Matplotlib etc. Solid understanding of machine learning concepts, algorithms. Experience with REST APIs and building scalable backend services. Familiarity with database technologies (e.g., PostgreSQL, MongoDB, SQL/NoSQL). Familiarity/experience with Cloud technologies(AWS, GCP, Azure etc.). Experience with version control systems, particularly Git. Strong problem-solving skills, analytical abilities, and attention to detail. Excellent communication and collaboration skills, with the ability to explain complex technical concepts clearly.

Preferred Skills and Qualifications (Nice to Have):

Hands-on experience with Large Language Models (LLMs) using RAG and their application in real-world scenarios. Familiarity with data quality and data governance concepts. Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related technical field. Design, develop, and maintain core functionalities and backend services using Python, focusing on AI and LLM integration. Integrate Large Language Models (LLMs) such as OpenAI, GPT, Llama, or others into applications to create intelligent, AI-powered features. Explore and apply LLM capabilities, including summarization, classification, RAG (Retrieval-Augmented Generation), prompt engineering, and prompt pipelines. Develop and implement efficient data processing pipelines for structured and unstructured data, ensuring data quality for AI models. Collaborate with cross-functional teams (e.g., product managers, data scientists, DevOps) to define, design, and ship new AI features and integrate LLMs effectively. Write clean, maintainable, well-tested, and well-documented Python code, adhering to best practices and coding standards. Ensure the reliability, performance, scalability, and security of AI/LLM-based applications, identifying and correcting bottlenecks. Conduct technical analysis of tasks, participate actively in scrum meetings, and deliver value committed for sprints. Stay up-to-date with the latest advancements in generative AI, LLM architectures, machine learning, and related technologies, sharing insights with the team. Participate in code reviews, contribute to technical improvements, and assist in troubleshooting and debugging issues.