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Professional experience: At least 6 years of professional software engineering experience, including substantial backend development and hands-on responsibility for production systems. Candidates should demonstrate recent practical development experience, including significant production changes delivered within the past 30 days.
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Programming skills: Strong proficiency in Go (Golang) and working proficiency in Python, with experience designing, developing, testing, and operating production-grade services.
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Event-driven systems: Hands-on experience building and operating event-driven or message-based architectures using technologies such as NATS, Kafka, or similar platforms. Knowledge of message contracts, idempotent consumers, replay, back-pressure, and reliable event delivery is important.
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CI/CD engineering: Practical experience developing and maintaining CI/CD pipeline tooling, including jobs, reusable templates, and runners. Experience managing GitLab CI at scale is a strong advantage.
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Application security: Strong working knowledge of web application security and the OWASP Top 10, with the ability to identify vulnerabilities in real code, implement fixes, and develop automated checks to prevent recurrence.
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Security scanning tools: Hands-on experience with SAST, SCA, and secret-scanning solutions such as Semgrep, CodeQL, Snyk, Trivy, Grype, or Gitleaks. The ability to tune these tools to deliver actionable findings while minimizing false positives is essential.
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Cloud-native technologies: Working knowledge of AWS and Kubernetes as deployment environments, including experience building, deploying, and operating secure services in cloud infrastructure.
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AI-assisted engineering: Demonstrated practical use of AI development tools such as Claude Code, Codex, Cursor, or custom large language model integrations. Experience building reusable, AI-powered workflows adopted by other engineers is particularly valuable.
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Security automation: Ability to translate manual security activities into reliable, scalable workflows that improve finding validation, remediation, verification, and reporting.
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Preferred industry experience: Experience in fintech, payments, buy now, pay later (BNPL), consumer lending, or other regulated environments is an advantage.
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Compliance awareness: Familiarity with PCI DSS and SOC 2 requirements as they relate to software development, change management, security controls, and audit evidence.
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Software supply-chain security: Knowledge of software bill of materials (SBOM) pipelines, dependency governance, artifact signing, and provenance technologies such as Sigstore and SLSA is beneficial.
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Policy-as-code: Familiarity with policy-as-code and admission-control tools such as Open Policy Agent (OPA), Kyverno, or Conftest is a plus.
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Security assessment experience: Exposure to bug bounty reports, external vulnerability triage, or system-level threat modeling is desirable.
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Engineering mindset: Strong analytical and problem-solving skills, a commitment to code quality, and the ability to design solutions that prevent entire classes of vulnerabilities rather than addressing isolated findings.
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Ownership and execution: A proactive approach to delivering results, resolving issues permanently, and maintaining high engineering standards while making pragmatic, timely decisions.
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Communication and teamwork: Ability to collaborate effectively with multidisciplinary teams, challenge technical decisions constructively, communicate clearly, and balance security objectives with business needs.
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Education: A bachelor's degree in Computer Science, Computer Engineering, or a related technical discipline is expected.
Benefits
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Competitive compensation: Gross monthly salary ranging from $5,000 to $9,500 USD, depending on experience, technical expertise, and expected contribution.
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Fully remote work: Work remotely from a location permitted by the employment arrangement, with the flexibility to work where you are most productive.
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High-impact engineering: Build and own security platform services that help protect production systems and improve security across the software development lifecycle.
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Modern technology stack: Work with Go, Python, AWS, Kubernetes, NATS, GitLab CI, MySQL, PostgreSQL, and Elasticsearch.
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AI-driven development: Opportunities to build and use AI-assisted engineering workflows that improve code reviews, vulnerability triage, remediation, and developer productivity.
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Technical autonomy: Take ownership of meaningful engineering projects, make architectural decisions, and drive improvements from design through production operation.
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Collaborative engineering culture: Work alongside specialists in security, detection and response, networking, and infrastructure engineering.
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Continuous learning: Develop expertise in cloud-native architecture, application security, event-driven systems, CI/CD automation, and emerging AI technologies.
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Quality-focused environment: Contribute to a culture that values automated testing, maintainable code, open-source technologies, practical innovation, and continuous improvement.
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Meaningful impact: Help establish scalable security practices that reduce recurring vulnerabilities and enable engineering teams to deliver software safely and efficiently.a