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CUBE, a global RegTech leader, is hiring a Python AI backend engineer in Bengaluru. You will design scalable AI-powered data ingestion pipelines, build web crawlers, and develop REST APIs to support AI services.
You will work with a cross-functional team spanning Product, Data Science, DevOps, and Engineering to deliver production-ready AI solutions that process structured and unstructured data at scale. The role emphasizes exploring NLP, document processing, and integration of LLMs, with an
CUBE are a global RegTech business defining and implementing the gold standard of regulatory intelligence for the financial services industry. We deliver our services through intuitive SaaS solutions, powered by AI, to simplify the complex and everchanging world of compliance for our clients.
CUBE is a globally recognized brand at the forefront of Regulatory Technology. Our industry-leading SaaS solutions are trusted by the world’s top financial institutions globally.
In 2024, we achieved over 50% growth, both organically and through two strategic acquisitions. We’re a fast-paced, high-performing team that thrives on pushing boundaries—continuously evolving our products, services, and operations. At CUBE, we don’t just keep up we stay ahead.
We believe our future is built by bold, ambitious individuals who are driven to make a real difference. Our “make it happen” culture empowers you to take ownership of your career and accelerate your personal and professional development from day one.
With over 700 CUBERs across 19 countries spanning EMEA, the Americas, and APAC, we operate as one team with a shared mission to transform regulatory compliance. Diversity, collaboration, and purpose are the heartbeat of our success.
We were among the first to harness the power of AI in regulatory intelligence, and we continue to lead with our cutting-edge technology. At CUBE, You will work alongside some of the brightest minds in AI research and engineering in developing impactful solutions that are reshaping the world of regulatory compliance.
Deliver scalable AI-enabled data ingestion and processing services.
Build reliable pipelines for extracting, transforming, and processing large volumes of structured and unstructured data.
Successfully deploy AI/ML models or LLM-powered services into production.
Ensure high system availability, performance, and operational visibility.
Deliver clean, maintainable, well-tested, and production-ready code.
Design, develop, and maintain scalable AI-powered data ingestion and processing platforms using Python. Build intelligent data pipelines, web crawling solutions, and AI/ML services that process structured and unstructured data while ensuring scalability, performance, and reliability.
Day 30: Understand the AI platform, data processing architecture, and development standards.
Deliver enhancements to backend services or AI processing pipelines.
Day 60: Independently build and deploy AI-powered data processing components and APIs.
Integrate AI/ML models into production workflows with monitoring and logging.
Day 90: Own end-to-end delivery of AI-enabled backend services and data pipelines.
Optimize model inference, pipeline performance, and system reliability.
Experience with RAG (Retrieval-Augmented Generation) architectures.
Knowledge of vector databases such as Pinecone, Weaviate, Milvus, or pgvector.
Experience with Hugging Face Transformers, PyTorch, or TensorFlow.
Exposure to MLOps tools such as MLflow, Kubeflow, or model serving frameworks.
Experience with Kubernetes and cloud-native deployments.
Knowledge of OCR, computer vision, or multimodal AI models.
If you are passionate about leveraging technology to transform regulatory compliance and meet the qualifications outlined above, we invite you to apply. Please submit your resume detailing your relevant experience and interest in CUBE.
CUBE is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.