Software Engineer (Data & AIML)

Design and build scalable, distributed data and AI architecture including reusable data products and production-grade AI/ML solutions such as prediction, GenAI/LLM, and agentic AI.

Develop and productionise reliable batch, streaming, and near-real-time data pipelines ensuring data quality, governance, lineage, metadata, security, and observability.

Make architecture and technology decisions focusing on scalability, reliability, security, performance, cost, and establish strong engineering practices including testing, CI/CD, and production operations.

4+ years of experience in software engineering, data engineering, AI/ML engineering, or related field.

Strong programming skills in Java and Python; experience with Scala, Kotlin, or similar languages is a plus.

Experience designing and building scalable, distributed, data-intensive systems and contributing to or owning architecture and technical design for data or AI platforms.

Experience with data pipeline technologies (Kafka, Spark, Databricks, Flink or equivalent), relational and/or NoSQL databases, cloud platforms (Azure, AWS, or Google Cloud), and productionising ML models including GenAI/LLM applications.

Experienced in building reusable platform capabilities rather than one-off solutions, with a platform mindset focused on scalability and reusability.

Demonstrates strong understanding of data architecture, distributed systems, and AI capabilities including RAG, embeddings, vector search, tool calling, and agentic AI workflows.

Has worked in complex environments requiring architecture, technical design leadership, and establishing engineering standards, preferably with exposure to cloud-native, CI/CD, and production operations.