AI Software Engineer
Job Summary
Blaze Information Security is seeking an AI Software Engineer to build next-generation offensive security tools and AI-powered capabilities. The role involves designing production-grade systems for agentic pentesting, red teaming, and AI-assisted vulnerability discovery. You will collaborate with security practitioners to transform offensive knowledge into scalable, practical software solutions.
Responsibilities
- Design and build AI-powered offensive security tools
- Develop agentic pentesting and red team automation systems
- Create AI-assisted code review workflows for vulnerability discovery
- Maintain backend services, CI/CD pipelines, and LLM orchestration
- Collaborate with security practitioners to productionize security research
Required Skills
- 4+ years of production-grade software engineering experience
- Proficiency in Python and backend languages
- Experience with LLMs, RAG, and orchestration workflows
- Knowledge of CI/CD and modern software practices
- Strong problem-solving and builder mentality
Job Details
### Role Overview
Blaze is looking for an AI Software Engineer focused on Offensive Cybersecurity Tools and Capabilities to help us build the next generation of offensive security tools and AI-powered capabilities for cybersecurity usage. This role is for someone who wants to work where applied AI meets real-world adversarial thinking. You will design and ship production-grade systems that support areas such as agentic pentesting and red teaming, as well as AI-powered code review for novel vulnerability discovery. You will work closely with experienced security practitioners to turn offensive security knowledge into software that creates real leverage. This is not a research-only role, nor is it a generic AI engineering job.
### Key responsibilities
- AI-powered security tooling: Design and build AI-powered tools for internal and client-facing offensive security use cases.
- Develop systems that support agentic pentesting workflows, red team operations, and security automation.
- Build AI-assisted code review and analysis workflows focused on identifying vulnerabilities and high-risk patterns.
- Turn real security testing problems into scalable software.
- Research and production delivery: Evaluate models, frameworks, and workflows related to applied AI in offensive cybersecurity.
- Prototype quickly, validate what works, and productionize the strongest ideas.
- Balance the speed of experimentation with engineering quality, reliability, and maintainability.
- Contribute to the technical direction of AI-enabled offensive security capabilities.
- Engineering and collaboration: Build and maintain backend services, integrations, and automation pipelines.
- Work with LLM orchestration, RAG pipelines, CI/CD, and supporting infrastructure.
- Collaborate closely with pentesters, consultants, and technical leadership.
- Improve the performance, observability, and robustness of the systems you build.
### Required skills
- Minimum of 4 years of proven experience building production-grade software systems.
- Strong programming skills in Python and/or other backend-oriented languages.
- Experience with modern software engineering practices, including CI/CD.
- Familiarity with LLM-based applications, orchestration workflows, or RAG systems.
- Ability to move from ambiguous ideas to working, dependable tooling.
- Strong problem-solving skills and sound engineering judgment.
- A builder mentality, with the ability to combine experimentation with disciplined execution.
- Strong communication skills and the ability to work across engineering and security teams.
- Must be located in Portugal and legally employable there.
### Nice to have
- Experience building AI-enabled products, developer tools, or internal platforms.
- Familiarity with offensive security, application security, pentesting, or red team workflows.
- Exposure to fuzzing, code review, vulnerability research, or secure software engineering.
- Experience with Go, Rust, TypeScript, containers, or cloud infrastructure.
- Experience working in a startup and fast-moving technical environment.
- Prior experience in cybersecurity services or security product companies.
### KPI and success metrics
- Delivery of production-ready AI tooling.
- Speed and quality of experimentation-to-production cycles.
- Adoption and impact of tooling across internal teams and client-facing workflows.
- Reliability, maintainability, and usability of deployed systems.
- Contribution to Blaze's offensive security capabilities and technical differentiation.