Senior Agentic AI Developer

A technology company specializing in advanced cybersecurity research and R&D. The company works with customers to build secure products, combining in-depth security research, architectural design, and low-level software development across a wide range of technologies.

As a Senior Agentic AI Developer, you will own the architecture and technical direction of our Agentic AI Malware Analysis and Threat Intelligence System: a mission-critical, on-premises platform designed for high-security, air-gapped environments. You’ll own the code, staying 100% hands-on, driving how the system is both architected and brought to life in production.

You will drive the integration of Large Language Models (LLMs), multi-agent orchestration frameworks (ReAct-style), and autonomous agents with high-fidelity malware analysis toolchains, enabling automated reverse engineering, behavioral analysis, and threat attribution at scale.

Requirements

• Own the end-to-end architecture of a complex, multi-component system, including LLM pipelines, agent orchestration layers, static and dynamic analysis engines, and local CTI knowledge base integration

• Develop, design, and implement critical components across backend, infrastructure, and AI/ML layers

• Drive the development of agentic AI capabilities, leveraging LLMs, autonomous agents, and multi-agent orchestration frameworks (e.g., ReAct) for complex task execution in malware analysis workflows

• Integrate AI systems with traditional reverse engineering toolchains, including binary analysis, disassemblers, debuggers, and sandbox environments

• Lead LLM fine-tuning and adaptation on domain-specific datasets such as malware samples, CTI feeds, and behavioral telemetry

• Design and implement systems for air-gapped/on-prem deployments, including model lifecycle management, secure update mechanisms, data isolation, and system hardening

• Translate advanced research into production-grade systems, turning prototypes into scalable, reliable, and interpretable solutions

• Set and enforce a high technical standard, reviewing outputs such as YARA rules, feature extraction pipelines, model outputs, and system architecture decisions

• Ensure explainability and reliability of AI outputs, including generating human-readable analysis of complex behaviors and attack chains

Skills and Experience

• 5+ years of experience in software engineering, with proven ownership of architecture and system design for complex distributed systems

• Strong hands-on experience with low-level programming (C++ required, Rust is a strong advantage)

• Deep expertise in reverse engineering, including both manual and automated techniques, with experience in low-level systems analysis and feature extraction from binaries

• Proven experience working with LLMs, Deep Learning models, and ML pipelines, including fine-tuning, evaluation, and deployment in production environments

• Experience with multi-agent systems, autonomous agents, and orchestration frameworks (e.g., ReAct or similar paradigms)

• Strong background in ML engineering applied to security data, such as binary analysis, network traffic analysis, and CTI ingestion pipelines

• Experience designing systems for air-gapped or highly restricted environments, including secure infrastructure, isolation techniques, and offline model/data management

• Ability to operate across the full stack: from system architecture and workflow orchestration down to hands-on implementation and debugging

• High ownership, strong problem-solving capabilities, and the ability to drive ambiguous, complex challenges to completion

• Meticulous attention to detail, with a focus on accuracy, consistency, and interpretability of outputs