Embedded Software Engineer

Blueprint Technologies•Redmond, WA

13d•$65 - $75•Hybrid

About The Position

As an Embedded Software Engineer, you will help build and evolve an advanced platform that automates firmware security analysis using modern compiler technologies, fuzzing frameworks, and AI-assisted workflows. You will develop scalable tools that transform firmware into analyzable intermediate representations, automate vulnerability discovery, and improve the accuracy and efficiency of security analysis pipelines. This role combines systems programming, compiler engineering, firmware security, and machine learning techniques to solve complex security challenges. You'll collaborate with engineers and security researchers to prototype new capabilities, harden them for production, and contribute to an open-source-ready developer platform.

Requirements

Bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, or a related technical field, or equivalent practical experience.
7+ years of professional experience developing systems software using C and/or C++.
5+ years of experience working with LLVM, compiler infrastructure, compiler development, or program analysis.
3–5+ years of experience with fuzzing, vulnerability research, or application security.
Experience developing compiler passes, static analysis tools, or code transformation frameworks.
Strong understanding of LLVM IR and compiler optimization concepts.
Experience debugging low-level software, memory corruption issues, and complex system behavior.
Proficiency with Python for automation, tooling, or pipeline development.
Experience working in Linux development environments.
Strong problem-solving skills with the ability to debug across compiler, firmware, and systems software layers.
Experience working with Git and modern software development practices.

Nice To Haves

Experience with firmware security, embedded systems, or bare-metal software development.
Knowledge of firmware architectures, hardware abstraction layers (HALs), MMIO, or firmware rehosting techniques.
Experience using fuzzing technologies such as libFuzzer, AFL, or AFL++.
Experience with sanitizer technologies including AddressSanitizer (ASan), UndefinedBehaviorSanitizer (UBSan), or MemorySanitizer (MSan).
Experience with static analysis, dataflow analysis, call graph analysis, CodeQL, or similar security analysis frameworks.
Experience building developer platforms, CI/CD automation, or large-scale engineering tooling.
Familiarity with cross-compilation toolchains and embedded development workflows.
Experience integrating large language models (LLMs) or AI-assisted automation into developer or security tooling.
Experience contributing to open-source software projects.
Experience developing production-quality testing frameworks and automation infrastructure.
Ability to thrive in a research-oriented environment while delivering production-ready software.
Strong collaboration and communication skills with cross-functional engineering teams.

Responsibilities

Design, develop, and maintain automated firmware security analysis pipelines for vulnerability discovery.
Build low-level tooling using C++, Python, and LLVM to analyze firmware at scale.
Develop compiler passes and transformations to convert firmware into analyzable LLVM Intermediate Representation (IR).
Create, improve, and maintain fuzzing harnesses to maximize code coverage and uncover security vulnerabilities.
Investigate crashes identified during fuzzing campaigns and perform root-cause analysis.
Improve vulnerability detection accuracy by reducing false positives and enhancing automated analysis workflows.
Develop and enhance AI-assisted systems that classify firmware functionality and generate security analysis artifacts.
Debug firmware rehosting environments and resolve issues affecting automated analysis.
Collaborate with compiler engineers, software engineers, and security researchers to review architectures and validate security findings.
Design scalable automation, testing, and CI/CD workflows that improve development efficiency and platform reliability.
Improve code quality through testing, documentation, dependency management, and engineering best practices.
Contribute to release readiness, developer onboarding experiences, and open-source preparation activities.
Evaluate and integrate new compiler, security, and AI technologies that improve platform capabilities.