Security Researcher And Developer

Description

We are looking for a senior software engineer to take a central role in building an advanced system for automated malware analysis and threat intelligence. This is a hands-on, high-impact position focused on designing and developing core technology from the ground up, at the intersection of cybersecurity, software engineering, and applied AI.

The role involves deep technical ownership: building systems that analyze malicious software at scale, extracting meaningful intelligence, and automating complex investigative workflows. You will work on real-world security problems, turning raw data and malware samples into actionable insights using modern engineering and machine learning approaches.

What You’ll Do

You will design and develop end-to-end solutions for automated malware analysis and threat detection, with a strong emphasis on practical, production-grade systems. This includes building analysis pipelines, integrating machine learning models (including LLM-based or agent-driven workflows where appropriate), and connecting results into threat intelligence platforms.

The work requires hands-on malware analysis and reverse engineering, combining static analysis and low-level understanding with scalable software design. You will handle large volumes of samples, indicators of compromise, and telemetry data, and develop automated detection mechanisms such as YARA rules.

You’ll take ownership of components across the stack — from data ingestion and feature extraction to model deployment and system integration — and apply strong analytical and systems thinking to solve complex, unstructured security problems.

Requirements

We’re looking for an experienced engineer with a strong software foundation and a cybersecurity background.

• 5+ years of experience in software engineering or a related technical role (or equivalent depth of expertise).
• Strong hands-on experience with Python and Rust.
• Solid background in malware analysis and reverse engineering, including static analysis and low-level systems work.
• Experience building production systems that process security data at scale (malware samples, binaries, network data, or CTI feeds).
• Experience with machine learning in production environments is a strong advantage, especially when applied to security problems.
• Comfortable working independently, owning complex problems end to end, and operating in ambiguous problem spaces.