AI & Data Engineer

Accountabilities:

• Design, build, and deploy AI-driven applications and agentic systems capable of reasoning, information retrieval, and complex workflow execution.
• Develop and optimize Retrieval-Augmented Generation (RAG) pipelines and AI agents using frameworks such as LangChain and LlamaIndex.
• Work with large language models and transformer-based architectures, including GPT, Gemini, and Claude, applying advanced prompt engineering, fine-tuning, and context-window optimization techniques.
• Build semantic search and vector-based retrieval layers using technologies such as PGVector, embedding models, and Google indexing capabilities.
• Process and transform large-scale datasets using Python, Pandas, PySpark, or Scala to support AI and data-intensive applications.
• Design high-performance SQL solutions and scalable data warehouse architectures using platforms such as Snowflake or Redshift.
• Create dimensional data models optimized for low-latency AI consumption, scalability, and strong data quality.
• Develop clean, maintainable, production-ready software supported by robust CI/CD practices and ML observability.
• Explore advanced AI architectures, including multi-agent systems, multimodal applications, and long-context use cases.
• Contribute to the deployment and scaling of AI workloads in cloud environments, with opportunities to work across AWS and Google AI ecosystems.

Requirements:

• 5+ years of relevant professional experience in AI engineering, data engineering, machine learning, software engineering, or a closely related technical field.
• 2+ years of hands-on experience building and deploying AI-driven applications, with strong expertise in RAG pipelines and AI agents.
• Strong understanding of transformer architectures and practical experience working with modern LLMs such as GPT, Gemini, or Claude.
• Proven experience with advanced prompt engineering, model fine-tuning, context optimization, embeddings, and semantic search.
• Strong data engineering capabilities, including experience processing large datasets with Python, Pandas, PySpark, or Scala.
• Professional experience with Snowflake or Redshift and the ability to write advanced, performance-oriented SQL.
• Strong data modeling skills, particularly in designing dimensional models for high-quality, low-latency AI workloads.
• Experience writing clean, maintainable production code and implementing CI/CD and ML observability practices.
• A Bachelor's or Master's degree in Computer Science, Engineering, or a related discipline is preferred.
• Experience with multi-agent systems, AWS services such as Bedrock and Lambda, or Google Gemini for multimodal and long-context applications is highly desirable.
• Strong analytical, problem-solving, communication, and collaboration skills, with the ability to work independently in a remote environment.