Principal Engineer – Data Engineering, AI & Distributed Systems

Overview

Principal Engineer providing technical leadership across enterprise data platforms, distributed systems, cloud-native architectures, and AI/Generative AI solutions. The role shapes long-term technology strategy and advises senior leadership on complex, large-scale engineering initiatives.

What you'll do

• Own the strategic direction and modernization of enterprise data platforms.
• Design scalable batch, streaming, real-time, lakehouse, and data mesh architectures.
• Govern enterprise software architecture using Java, Spring Boot, microservices, REST APIs, and distributed systems.
• Lead enterprise-scale Generative AI, RAG, agentic AI, and LLM-powered solutions.
• Define standards for security, governance, observability, quality, lineage, and compliance.
• Lead cloud strategy, platform engineering, modernization, resiliency, and disaster recovery initiatives.
• Influence architecture decisions, technology investments, roadmaps, and senior stakeholders.

What you'll need

• At least 7 years of engineering experience or equivalent experience, training, military experience, or education.
• At least 7 years of software engineering experience with significant leadership responsibilities.
• At least 7 years designing and delivering large-scale data engineering solutions.
• At least 7 years leading cloud-native architectures.
• At least 3 years of hands-on Generative AI implementation experience.
• Expertise in data engineering, Java/Spring Boot microservices, distributed systems, and Generative AI.
• Experience with technologies including Spark, Kafka, Snowflake, Databricks, Azure or GCP, Docker, and Kubernetes.

Nice to have

• Experience training, fine-tuning, and deploying LLMs in enterprise environments.
• Experience with enterprise AI governance, responsible AI, and legacy-to-cloud modernization programs.
• Experience supporting finance, treasury, risk, or regulatory functions.

Details

• Location: Bengaluru, India.