Senior AI Engineer

Location: Bengaluru, India

Department: Data & AI

• Design and build production-grade ML models for credit underwriting, risk scoring, and fraud detection on TB-scale transaction data.
• Architect and maintain low-latency AI inference pipelines integrated with UPI payment flows and the CLOU credit lifecycle.
• Lead the AI feature roadmap for one or more product domains - from problem framing through deployment and monitoring.
• Evaluate and integrate LLM and GenAI capabilities into internal tooling, operations automation, and customer-facing features.
• Build and maintain robust data pipelines (ClickHouse, Spark, Kafka) that feed model training and real-time inference.
• Define and enforce ML engineering best practices — versioning, experimentation frameworks, model observability, and drift detection.
• Collaborate directly with product, credit, and engineering teams to translate business problems into scalable AI solutions.
• Mentor L1/L2 engineers; conduct design and code reviews; raise the technical bar across the team.

• 5+ years of hands-on software engineering experience with at least 3 years focused on ML/AI systems in production.
• Strong foundations in machine learning - supervised/unsupervised learning, gradient boosting (XGBoost, LightGBM), deep learning, and model evaluation.
• Proficiency in Python and the ML ecosystem: PyTorch or TensorFlow, scikit-learn, MLflow or similar experiment tracking.
• Experience with real-time and batch data infrastructure: Kafka, Spark, Flink, ClickHouse, or equivalent.
• Familiarity with LLM APIs, prompt engineering, RAG architectures, and embedding-based systems.
• Solid software engineering fundamentals - clean code, distributed systems, REST/gRPC APIs, containerisation (Docker/Kubernetes).st product.
• Experience in fintech, payments, lending, or credit is a strong plus — understanding of risk, compliance, and regulated data environments.
• Customer obsession - you think about end-user impact, not just model metrics.
• Highest standards - you are not satisfied shipping 80%; you care about correctness, reliability, and edge cases.
• Full ownership - you treat problems as yours until they are solved, not until the code is merged.
• AI-native - you actively use AI tools in your own workflow and push the team to build AI-first by default.

• Experience with credit scoring models, bureau data (CIBIL, Experian), or alternative data underwriting.
• Contributions to open-source ML projects or published research.
• Familiarity with NPCI's UPI ecosystem, RBI regulatory guidelines for digital lending, or CLOU product architecture.

• Work on real-world, high-scale systems in banking, credit, and payments
• Solve complex engineering problems that directly impact millions of end users
• Collaborate with strong engineers and product leaders who care about quality and speed
• High ownership from day one - build, ship, and see your work in production
• Opportunity to shape systems, not just contribute to them