Senior Principal Software Archjtect

Two Six Technologies•Arlington, VA

3h•Hybrid

About The Position

At Two Six Technologies, we build, deploy, and implement innovative products that solve the world’s most complex challenges today. Through unrivaled collaboration and unwavering trust, we push the boundaries of what’s possible to empower our team and support our customers in building a safer global future. Overview of Opportunity Two Six Technologies seeks a skilled Senior Principal Software Architect specializing in AI-Augmented security systems to support our growing team of experts in vulnerability research, reverse engineering, and exploit development. This role involves automating cutting-edge security research on mobile applications and operating systems, with a specific focus on Android platforms and wireless communication systems.

Requirements

Bachelor’s degree in Computer Science or a related technical field (strong relevant experience may substitute for specific degree).
Minimum of 12 years of experience in software development with low-level programming (C and at least one assembly language), scripting (e.g., Python), and nix command-line proficiency.
Architectural Pattern Proficiency: knowledge of Event-Driven Architecture (EDA) and Microservices. Automating Human-in-the-Loop (HITL) processes that usually requires asynchronous workflows and robust message queuing (e.g., Kafka, RabbitMQ).
Orchestration Experience: Knowledge of how to chain AI actions while maintaining state (i.e. LangChain, LlamaIndex, or Temporal)
LLM Integration & Context Engineering: Experience with RAG (Retrieval Augmented Generation), MCP (Model Context Protocol), and agent skills.
API Design: The ability to build robust, scalable APIs that can handle the unpredictable latency of AI inference.
Cost Management: Experience in optimizing token usage and choosing between high-cost frontier models and cheaper, local models for specific tasks.
Ability to obtain a Top Secret clearance

Nice To Haves

UI/UX Intuition: experience or understanding of how to build “Human-in-the-loop” dashboards.
Reverse Engineering Tooling Integration: Experience building plugins or integrations for Ghidra, IDA Pro, Binary Ninja or similar tools.
Fuzzing Automation: Knowledge of how to use AI to generate “smarter” seeds for fuzzers like AFL++ or LibFuzzer to reach deep code paths.
Custom Model Fine-tuning: Experience fine-tuning smaller, local LLMs on CodeQL or specific assembly languages (ARM, x86) to detect patterns that general models miss.
Guardrails & Validation Logic: experience implementing automated evaluation (LLM-as-a-judge) and fallback mechanisms when the AI confidence score is low.
Sandboxing & Execution Security: processing malicious or untrusted code, the architect must have a level of proficiency in secure orchestration (e.g., Firecracker microVMs, gVisor, or hardened Docker).
High-Fidelity Context Injection: Proficiency in building RAG pipelines that pull from various levels of technical documentation rather than just general web text.
Explainability (XAI): A researcher won't trust an AI that says “this is a bug” without proof. The architect must design systems that provide provenance, such as linking AI findings back to specific lines of code or memory addresses.
Knowledge of Android OS internals and current security exploitation techniques.
Familiarity with modern web browser internals and security practices.
Experience with wireless communication systems (e.g., Bluetooth, Wi-Fi, cellular) and their interactions with mobile devices.
Proficiency in ARM, x64, and PowerPC architectures, with hands-on experience in reverse engineering and a deep understanding of special registers, memory layouts, and exploitation techniques across these systems.
Expertise in software reverse engineering, including static and dynamic analysis, and fuzzing techniques.
Experience with vulnerability research, such as attack surface assessment, vulnerability discovery, and proof-of-concept development to demonstrate security impact.
Previous experience in a client-facing technical role.

Responsibilities

Experience designing and implementing modular, scalable system architectures that align technical infrastructure with evolving research and operational requirements.
Build fault-tolerant AI pipelines where LLM outputs drive complex system actions, ensuring robust state management and error-handling in non-deterministic environments.
Work closely with security researchers to automate techniques to identify vulnerabilities, trigger them efficiently, and optimize exploitation processes.
Leverage AI/LLMs to automate repetitive tasks across the research lifecycle, from initial data gathering to the generation of technical artifacts.