AI Malware Engineer
Location: London, UK
Department: Research & Engineering
Company: AI Cybersecurity Startup — AI-Powered Binary Analysis Platform
About Us
We are building an AI-native binary analysis and reverse engineering platform designed to transform how malware analysis, threat research, and vulnerability discovery are performed. Our platform combines large language models, program analysis, symbolic reasoning, and automated reverse engineering to accelerate malware triage and enable scalable threat intelligence workflows. Our mission is to augment human analysts with AI-driven tooling capable of understanding binaries, deobfuscating malware, automating reverse engineering tasks, and generating actionable intelligence at machine speed.
We are looking for a Malware Engineer who combines deep malware analysis expertise with modern AI and automation capabilities.
Role Overview
As an AI Malware Engineer, you will develop intelligent analysis pipelines that automate malware triage, reverse engineering, unpacking, classification, and behavioral analysis using AI models and program analysis techniques.
You will work at the intersection of:
- Malware research
- Reverse engineering
- Applied AI/LLMs
- Binary analysis
- Automation engineering
- Threat intelligence
This role is ideal for someone who understands malware internals and is excited about building AI systems that augment or automate analyst workflows.
Responsibilities
- Analyze malware samples across Windows, Linux, macOS, mobile, and cloud environments
- Reverse engineer binaries using tools such as IDA Pro, Ghidra, Binary Ninja, and x64Dbg
- Build AI-assisted malware analysis workflows and automation pipelines
- Develop systems that leverage LLMs and AI agents for function classification, malware family identification, behavioral summarization, and IOC extraction.
- Create scalable pipelines for static and dynamic analysis, YARA generation
- Integrate AI models with binary analysis frameworks and disassemblers
- Fine-tune or evaluate models for reverse engineering and malware analysis tasks
- Build tooling for unpacking, emulation, instrumentation, and malware execution tracing
- Research new malware techniques, evasion methods, and anti-analysis behaviors
- Collaborate with platform engineers and researchers to improve AI-assisted reverse engineering capabilities
- Contribute to internal datasets, benchmarks, and malware knowledge graphs
- Produce high-quality technical writeups and threat intelligence reports
Required Qualifications
- Strong experience in malware analysis and reverse engineering
- Deep understanding of Windows internals, PE/ELF/Mach-O formats, Assembly language (x86/x64/ARM), Operating system internals, and Debugging and memory analysis
- Experience with malware tooling and workflows
- Proficiency in Python for automation and tooling development
- Experience building analysis pipelines and automation systems
- Familiarity with AI/ML concepts and modern LLM workflows
- Experience using APIs and orchestration frameworks for AI agents and automation
Preferred Qualifications
- Experience applying LLMs to cybersecurity or reverse engineering workflows
- Experience with AssemblyLine, ANGR, Capstone, QEMU, or Frida
- Familiarity with retrieval-augmented generation (RAG), embeddings, and vector search
- Knowledge of malware clustering and similarity analysis
- Experience building autonomous or semi-autonomous security agents
- Understanding of symbolic execution or program analysis techniques
- Background in threat intelligence or detection engineering
- Contributions to open-source security tooling or malware research
What You’ll Work On
- AI-powered malware triage systems
- Autonomous reverse engineering agents
- Binary embedding and similarity search systems
- AI-assisted decompilation and function annotation
- Intelligent unpacking and deobfuscation workflows
- Malware family clustering and attribution systems
- Scalable cloud malware analysis infrastructure
- Analyst copilots for reverse engineering workflows
Tech Stack
Examples of technologies we use include:
- Python, Rust, C++
- AssemblyLine
- PyTorch, Transformers, vLLM
- IDA Pro SDK, Ghidra APIs, Binary Ninja APIs
- LLVM, angr, Capstone, Triton
- Docker, Kubernetes
- Vector databases and knowledge graphs
- GPU inference infrastructure
- Malware sandboxing frameworks
Ideal Candidate
You are someone who:
- Loves reverse engineering and understanding how malware works
- Thinks deeply about automation and analyst augmentation
- Is excited about applying AI to difficult low-level security problems
- Enjoys building practical tooling, not just research prototypes
- Can move fluidly between malware analysis, engineering, and applied AI
- Wants to help define the future of AI-driven cybersecurity
Why Join Us
- Work on cutting-edge AI and reverse engineering problems
- Build technology that fundamentally changes malware analysis workflows
- Small, highly technical team with significant ownership
- Opportunity to shape core platform architecture and research direction
- Competitive compensation, equity, and flexible working environment
Example Keywords for Applicants
- Malware Analysis • Reverse Engineering • AI Security • Binary Analysis • LLMs • Threat Intelligence • Automation • Program Analysis • Ghidra • IDA Pro • Python • Sandboxing • Deobfuscation • Cybersecurity Research