Senior Software Engineer, Data Platform & AI Enablement Engineering

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Company Overview

A leading global financial technology organization is building a unified payments and financial platform that enables businesses worldwide to manage accounts, payments, spend management, treasury, and embedded finance through a single integrated solution. With a global workforce spanning multiple international offices, the company is focused on delivering scalable financial infrastructure and advancing the future of global banking through innovation in data, artificial intelligence, and machine learning.

The organization is seeking a Senior Software Engineer, Data Platform & AI Enablement Engineering to help shape the future of its data and AI ecosystem. This role will focus on designing and building foundational infrastructure that empowers teams across the business to leverage data, AI, and machine learning to drive measurable business impact.

The successful candidate will lead the development of high-performance distributed systems, contribute to AI-ready platform capabilities, and provide technical leadership across large-scale engineering initiatives. This position offers the opportunity to work on cutting-edge technologies spanning data platforms, real-time systems, and AI-driven products.

About the Team

The Knowledge Platform team is responsible for developing the infrastructure that supports the organization’s data and AI strategy. The team manages the complete data and AI/ML lifecycle, including data infrastructure, data-serving technologies, and governance platforms for AI and machine learning models.

Its mission is to evolve the company’s data ecosystem into a fully AI agent-ready platform, enabling users to derive actionable insights through analytics, natural language querying, and real-time decision-making capabilities.

Key Responsibilities

• Lead the architecture and development of core infrastructure components across data and AI platforms.
• Own technical decision-making and custom development efforts, from foundational storage systems to highly available service layers.
• Perform deep analysis of system internals and optimize performance related to state management, checkpointing, and exactly-once processing semantics.
• Build and scale the Knowledge Platform to support AI-powered products through vector indexing, agentic workflows, and real-time data streaming.
• Manage the full software development lifecycle for distributed systems processing petabytes of data across more than 30 global regions.
• Champion engineering excellence by contributing to shared tooling, SDKs, and automation frameworks.
• Mentor and support mid-level engineers through design reviews, technical guidance, and hands-on leadership.
• Drive the adoption of best practices in software engineering, reliability, and platform scalability.

Required Qualifications

• 5+ years of experience building and operating large-scale distributed systems or infrastructure platforms.
• Strong foundation in computer science concepts, including distributed systems, memory management, and networking protocols.
• Proficiency in Java, Kotlin, or Go.
• Experience with, or a strong interest in, technologies such as Kafka, Flink, Spark, Kubernetes, and OLAP engines.
• Demonstrated ability to take ownership of complex technical challenges from design through production deployment.
• Strong interest in AI/ML infrastructure and real-time systems with a focus on delivering business value.
• Excellent written and verbal communication skills with the ability to engage technical and non-technical stakeholders.
• Ability to thrive in fast-paced and complex environments.

Preferred Qualifications

• Experience designing data processing patterns for modern Lakehouse architectures.
• Hands-on experience developing frameworks, services, and client libraries for big data platforms.
• Familiarity with technologies including GCP, Databricks, BigQuery, DataProc, Kafka, Kubernetes, Spark, DataFlow, Google Cloud Storage, and Airflow.
• Ability to evaluate emerging technologies and conduct proof-of-concept initiatives to influence architectural decisions.
• Experience contributing to scalable, enterprise-grade data and AI platforms.

Disclaimer

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