Degree in Computer Science, Engineering, Mathematics, or equivalent experience
2+ years of professional experience in building and deploying data solutions and software products
Strong coding skills in Python, with additional experience in Scala or Java being a plus
Experience working with structured, semi-structured, and unstructured data
Hands-on expertise in containerization and orchestration using Docker and Kubernetes for scalable production systems
Familiarity with distributed computing frameworks (e.g., Spark, Dask), cloud platforms (e.g., AWS, Azure, GCP), and analytics libraries (e.g., pandas, numpy, matplotlib)
Exposure to DevOps, DataOps, and MLOps concepts and best practices. Experience with core technologies such as Python, PySpark, SQL, Airflow, Databricks, Kedro, Dask/RAPIDS, Docker, Kubernetes, and cloud services (AWS/GCP/Azure)
Experience with Generative AI (GenAI) or agentic systems, including building Retrieval-Augmented Generation (RAG) systems, implementing large language models (LLMs), or integrating advanced AI frameworks is a plus
Exposure to AI modeling frameworks such as TensorFlow, PyTorch, Keras, or Scikit-Learn, along with familiarity with AI Governance and Safety principles, including Responsible AI practices, bias and hallucination testing, and LLM safety guardrails
Demonstrated experience working collaboratively with other developers, as well as technical and non-technical people within software teams
Experience working in Agile teams, including active participation in sprint ceremonies
Exceptional time management to meet your responsibilities in a complex and largely autonomous work environment
Strong communication skills, both verbal and written, in English and local office language(s), with the ability to adjust your style to suit different perspectives and seniority levels
