Senior Software Engineer/Tech Lead for real-time video analysis startup

Senior Software Engineer

Location: Caesarea / Hybrid   

Experience: 10+ years

Start: Immediate

Compensation: Equity Plan Available

About Argu

Argu turns passive CCTV cameras into proactive Agents, used by some of the world's most known organizations, cities and governments to protect and manage valuable assets and operations using real-time video. We're backed by some of the world's leading investors including a16z and governments that are sharing our vision of an agentic, autonomous video understanding at scale.

The Role

We are seeking a Senior Software Engineer with 10+ years of experience in backend engineering, scalable systems, and real-time environments, ideally experienced within real-time, unmanned, mission-critical systems where performance and latency are paramount.

This is a high-ownership, end-to-end role with full responsibility for the architecture and development of core systems. You will design, build, and implement pipelines, features, and foundational backend infrastructure. The role is primarily backend-focused, with just enough frontend capability to independently deliver easy UI components when needed, ensuring fast, uninterrupted execution without external dependencies.

You will work hands-on within the codebase, architecting scalable/micro services, developing modular and self-contained components, and integrating AI model outputs into production-grade pipelines. The position involves close collaboration with the CTO and research team in a fast-paced, low-bureaucracy environment, supporting real-world deployments and enterprise customers, while maintaining the highest degree of verification and testing to make sure nothing breaks in production.

What You’ll Do

• Design and own backend architecture - build scalable, distributed systems and components that are self-contained, well-abstracted, and independently deployable.

• Build and maintain backend APIs, asynchronous data pipelines, and processing services that operate reliably at scale in production.

• Design and optimize systems for low-latency, real-time decision-making, where performance directly impacts production outcomes.

• Integrate AI model outputs (detection, classification, video analysis) into robust, production-grade product experiences.

• Work with video processing pipelines - ingest, process, and route live video streams as a core part of the platform.

• Ship frontend changes when needed - build minimal but functional UI components (e.g. dashboards, flows, controls) to unblock delivery without relying on a dedicated frontend engineer.

• Collaborate closely with the CTO and research team to bridge the gap between model capability and production-ready systems.

• Drive technical decisions across system design, service boundaries, and reliability — owning outcomes end-to-end.

• Own reliability end-to-end - from system design and testing through deployment, monitoring, and production stability.

• Conduct code reviews, peer-to-peer evaluations and serve as a knowledge center for the product's backbone and backend infra.

Required Skills

• Strong Python backend development - APIs, async pipelines, clean architecture, and system design.

• Deep understanding of backend architecture: service boundaries, data flow, scalability patterns, and building systems that operate reliably under real-world constraints.

• Experience building or working with real-time and/or low-latency systems.

• Experience with video processing or streaming - familiarity with RTSP, FFmpeg, live video pipelines, or similar media infrastructure.

• Experience integrating AI/ML model outputs into production systems - understanding how models interface with real-world applications.

• Frontend knowledge in React and TypeScript - comfortable shipping small but complete UI features independently.

• Experience shipping and maintaining production systems with real users and high reliability requirements.

• Comfort working across the stack and quickly ramping up in new technical domains.

• Ability to drive technical direction, document decisions, and maintain alignment between architecture, implementation, and product goals.

Bonus

• Experience with Docker-based deployments (cloud or on-prem).

• Background in computer vision or ML-adjacent products.

• Experience in industrial, security, or enterprise environments.

• Experience designing event-driven or message-queue architectures at scale.

Who You Are

• You ship. You don’t wait for perfect specs - you ask the right questions, make decisions, and move forward.

• You think in systems. You care about how components behave and interact in production, not just getting a task done.

• You’re comfortable owning a feature end-to-end - from design through deployment and ongoing reliability.

• You care deeply about real-world performance, not just passing tests.

• You thrive in early-stage environments where autonomy and judgment are required.

• You’re someone we can trust to own critical parts of the system - and someone who's fun working with day-to-day.