Principal Engineer – Data Engineering, AI & Distributed Systems
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Protocol Intelligence
Data-driven signals on your job's competitivenessTier-1 brand and Bangalore metro increase competition, but niche senior GenAI/data focus limits applicant density.
Strong finance domain requirements plus enterprise data/GenAI expertise make industry background highly important.
Explicit 7+ years, finance/regulatory domain experience and mandated tech stack create strict shortlisting filters.
Job Description
Structured overview of role & requirementsAbout This Role
Lead the strategic direction and modernization of enterprise data platforms, distributed systems, AI/GenAI solutions, and cloud-native architectures at scale.
Architect and deliver large-scale data engineering, AI, and microservices solutions ensuring scalability, security, compliance, and operational excellence.
Serve as a technical advisor to senior leadership influencing technology investments, architecture decisions, and driving cross-functional alignment for critical business capabilities.
Minimum Requirements
Minimum 7+ years of engineering experience including significant leadership responsibilities.
7+ years designing and delivering large-scale data engineering solutions involving technologies like Apache Spark, Kafka, Snowflake, Databricks, etc.
3+ years hands-on experience with Generative AI including LLM training, deployment, and AI governance frameworks.
Experience with cloud-native architectures (Azure, GCP), Java/Spring Boot microservices, and mission-critical financial platforms.
Ideal Candidate Profile
Recognized technical leader with deep expertise in Data Engineering, Generative AI, and cloud-native distributed systems.
Proven ability to influence CIO/CTO/senior executives and lead large-scale modernization initiatives including legacy-to-cloud migration.
Comfortable operating in complex, regulated environments delivering scalable AI and data platforms aligned with business and risk objectives.