Construction Project manager

Software Design Engineer 4

A typical day on Project Talonera involves building and improving AI-driven firmware security analysis pipelines that automatically discover vulnerabilities in third-party firmware. Engineers spend their time developing low-level tooling in C++, Python, and LLVM, transforming firmware source code into analyzable LLVM IR, creating compiler passes, generating and refining fuzzing harnesses, and improving automated vulnerability detection workflows.

Daily work may include debugging firmware rehosting issues, investigating crashes discovered during fuzzing campaigns, reducing false positives in security findings, and enhancing LLM-based systems that classify firmware functionality and generate analysis artifacts. Team members collaborate closely with security researchers, compiler engineers, and project leadership to review architecture, prioritize new capabilities, and validate analysis results across diverse firmware targets.

As Talonera moves toward open-source release, engineers also contribute to code quality improvements, CI/CD automation, testing, documentation, dependency reviews, developer onboarding experiences, and release-readiness activities, helping transform advanced security research into a production-grade platform that can be used and extended by the broader security community.

Responsibilities

• Build and Enhance Security Analysis Pipelines
• Develop preprocessing pipelines that compile C/C++ firmware code into LLVM Intermediate Representation (IR).
• Implement and maintain LLVM-based transformations to make firmware suitable for off-target analysis and fuzzing.
• Create and improve code-analysis workflows, including call-graph extraction, metadata generation, and static-analysis integrations.
• Design and maintain systems that generate and execute fuzzing campaigns using modern fuzzing frameworks and AI-assisted techniques.
• Improve crash triage systems that automatically identify, deduplicate, and analyze security findings.
• Develop automated mechanisms to classify code semantics and improve analysis accuracy.
• Security Automation and Tooling
• Build scalable automation that combines compiler infrastructure, security tooling, and AI-driven workflows.
• Enhance vulnerability detection pipelines and help reduce false positives through improved analysis techniques.
• Improve reporting systems that transform raw security findings into actionable engineering insights.
• Validate analysis approaches across multiple firmware targets and environments.
• Open-Source Readiness
• Improve system reliability, modularity, test coverage, and CI/CD automation.
• Create developer documentation, onboarding guides, and architectural references.
• Support dependency review, reproducible builds, and general open-source readiness activities.
• Help establish contribution workflows, issue triage practices, and release processes for external contributors.
• Engineering Excellence
• Write clean, maintainable, and well-tested code.
• Participate in design reviews and technical architecture discussions.
• Collaborate closely with engineers across security, hardware, and platform teams.
• Contribute to long-term technical strategy and platform evolution.

Required Qualifications

• Bachelor's degree in Computer Science, Computer Engineering, or a related technical field, or equivalent practical experience.
• Strong professional experience developing software in C/C++.
• Hands-on experience with compiler technologies, LLVM, or low-level systems programming.
• Experience working with fuzzing frameworks such as libFuzzer, AFL, AFL++, or similar technologies.
• Strong understanding of software security principles, including memory-safety vulnerabilities and root-cause analysis.
• Proficiency with Python for automation and tooling development.
• Experience using Git-based development workflows.
• Demonstrated ability to write well-tested, maintainable, and documented production code.

Preferred Qualifications

• Experience with firmware, embedded systems, device software, or bare-metal development.
• Knowledge of hardware abstraction layers (HALs), MMIO, emulation, rehosting, or cross-compilation techniques.
• Experience with static-analysis platforms such as CodeQL.
• Familiarity with program-analysis concepts such as call graphs, data-flow analysis, or IR transformations.
• Experience integrating AI, machine learning, or LLM technologies into engineering workflows.
• Previous open-source contributor or maintainer experience.
• Experience building CI/CD pipelines and release automation.
• Familiarity with Azure DevOps, GitHub, or similar development platforms.

Ideal Candidate

The ideal candidate for Project Talonera is a systems software engineer with a strong security mindset who enjoys working at the intersection of compiler technology, firmware analysis, fuzzing, and AI-assisted automation. They likely have several years of professional experience developing low-level software in C/C++, are comfortable working directly with LLVM and LLVM IR, and have hands-on experience building or modifying compiler passes, analysis tools, or developer tooling.

What is the ideal background of a candidate for this role?

• Compiler and Program Analysis Engineering – experience with LLVM, code transformation, static analysis, CodeQL, call-graph analysis, dataflow analysis, or language tooling.
• Security Engineering and Research – experience with fuzzing (libFuzzer, AFL/AFL++), vulnerability discovery, crash triage, exploit mitigation, sanitizer technologies (ASan, UBSan, MSan), and root-cause analysis.
• Firmware or Embedded Systems Development – familiarity with firmware architectures, hardware abstraction layers (HALs), MMIO interfaces, cross-compilation, bare-metal systems, or rehosting techniques.
• Developer Platform and Tooling Engineering – experience building scalable automation pipelines, CI/CD systems, code-generation tools, testing frameworks, and production-quality open-source software.
• An ideal candidate is naturally curious and enjoys debugging difficult technical problems that span multiple domains—from understanding firmware internals and compiler behavior to improving AI-driven analysis workflows. They should be comfortable working in a research-oriented environment where ideas are rapidly prototyped and then hardened into reliable production systems. Experience integrating modern LLM-based workflows into developer tools or security pipelines is highly desirable, but deep expertise in AI is less important than having strong foundations in software engineering, security, and systems programming.
• Ultimately, the best fit is someone who can look at a complex firmware security challenge and think, "I can automate that," then build the compiler, fuzzing, and analysis infrastructure needed to make that automation reliable, scalable, and ready for open-source adoption.

Top 3 Must-Have HARD Skills

• LLVM / Compiler Engineering – 5+ years
• C/C++ Systems Programming – 7+ years
• Security Fuzzing & Vulnerability Research – 3–5+ years

Salary Range: $1,66,000 - 1,72,000 Annually - Factors that may affect pay within this range may include geography/market, skills, education, experience, and other qualifications of the successful candidate.

The Company offers the following benefits for this position, subject to applicable eligibility requirements: [medical insurance] [dental insurance] [vision insurance] [401(k) retirement plan] [long-term disability insurance [short-term disability insurance] [5 personal days accrued each calendar year. The paid time off benefits meet the paid sick and safe time laws that pertain to the City/ State] [10-15 days of paid vacation time] [6 paid holidays and 1 floating holiday per calendar year]

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