Staff Engineer

About Incode

Incode is a Series B unicorn ($1.25 B valuation) rewriting how the world proves identity. Our AI-powered platform lets leading banks, fintechs, marketplaces, and governments deliver friction-free experiences while defeating fraud and safeguarding privacy. Customers such as Citi, AirBnB, Block, Chime, Sixt, and TikTok rely on Incode to power their identity verification and security. Recently named a leader in the Gartner® Magic Quadrant™ for Identity Verification, we’re scaling fast—and we need a product-marketing leader who can turn breakthrough technology into a category-defining narrative.

The Impact You’ll Make

As a Staff Engineer, you’ll play a pivotal role in shaping the technical foundation behind mission-critical systems that power secure, seamless identity experiences for enterprises worldwide.

Embedded within a high-impact, high-ownership engineering team, you’ll drive end-to-end technical direction — from architecture and system design to hands-on implementation in production. You’ll partner closely with Engineering, Product, and cross-functional leaders across Tel Aviv, the US, and Serbia to solve some of the most complex challenges in fraud detection, real-time data processing, and AI-driven automation.

This is a deeply technical leadership role for someone who thrives at the intersection of distributed systems, large-scale infrastructure, and emerging AI technologies — and who leads through both vision and execution.

What You’ll Own & Drive

• Core Platform Architecture & Technical Strategy - Define and own the technical roadmap for foundational platform components powering fraud detection and identity verification at scale. Shape long-term architecture decisions that ensure reliability, scalability, and performance across mission-critical systems.
• Cross-Team Technical Leadership - Lead complex architectural initiatives spanning multiple engineering teams and geographies. Drive technical alignment, author design documents, facilitate decision-making, and build consensus across Engineering and Product stakeholders.
• Hands-On Engineering Excellence - Stay deeply involved in implementation — contributing production-grade code, raising engineering standards through example, and mentoring teams through technical leadership and execution excellence.
• Large-Scale Data & Streaming Systems - Design and evolve high-throughput distributed systems, including real-time, streaming, and batch data processing pipelines leveraging technologies such as Kafka, Flink, and Spark.
• AI-Driven Engineering Innovation - Drive ad