Description:
We are seeking a hands-on AI Engineer to join our BI & Development team. You will build AI-powered automation workflows and LLM applications that turn business processes into reliable systems. The role also includes supporting machine learning models that give stakeholders data-driven insights. The ideal candidate is a strong Python developer who is comfortable across automation, LLM orchestration, and machine learning, and who is eager to deepen their ML skills on the job.
Key Responsibilities
- Design, build, and maintain end-to-end automation workflows using n8n and similar tools (e.g., Make, Zapier, Airflow).
- Develop LLM-powered applications and agents using LangChain and LangGraph, including prompt design, tool calling, retrieval-augmented generation (RAG), and multi-step agent orchestration.
- Integrate AI models and services (OpenAI, Anthropic, open-source models) with business systems via APIs, webhooks, and databases.
- Support machine learning work, including data preprocessing, feature engineering, exploratory data analysis (EDA), and training and evaluating models using Scikit-learn or similar libraries.
- Extract and analyze data using SQL.
- Write clean, maintainable Python code for data processing, backend services, and automation logic.
- Deploy and monitor AI workflows and services in production, including logging, error handling, and cost/latency optimization.
- Evaluate and improve LLM output quality through testing, prompt iteration, and feedback loops.
- Collaborate with stakeholders to translate business problems into automated, AI-driven or data-driven solutions.
- Maintain code quality using Git version control and follow software development best practices.
- Document workflows, architectures, and integrations for handover and long-term maintenance.
Required Qualifications
- Bachelor’s degree in Computer Science, Data Science, Artificial Intelligence, Software Engineering, Statistics, or a related quantitative field.
- 1.5–2 years of professional experience in AI engineering, automation, backend development, or data science.
- Strong programming skills in Python and SQL.
- Hands-on experience with n8n or comparable workflow automation platforms.
- Practical experience building LLM applications with LangChain and/or LangGraph.
- Experience integrating REST APIs, webhooks, and third-party services.
- Working knowledge of machine learning concepts and libraries (e.g., Scikit-learn, Pandas, NumPy).
- Solid understanding of prompt engineering, embeddings, and vector databases.
- Strong analytical and problem-solving skills.
- Excellent communication and collaboration abilities.