Senior DevSecOps Engineer

This position is listed on behalf of a partner company, which manages all applications and next steps. Our partner is looking for a Senior DevSecOps Engineer based in Brazil . This role offers the opportunity to architect and secure the cloud infrastructure powering an enterprise-grade Agent Development Platform. You will build isolated, secure execution environments for autonomous AI agents while ensuring sensitive data remains protected at every stage. Working at the intersection of cloud engineering, cybersecurity, and AI infrastructure, you will design zero-trust connectivity, enforce strict network controls, and manage specialized databases that support advanced AI applications. You will lead AWS production environment setup, infrastructure automation, and event-driven orchestration for complex agent workflows. Collaborating with cross-functional engineering teams, you will help establish scalable, resilient, and security-first foundations for next-generation AI systems. This is an opportunity to make a meaningful impact on emerging technology while working remotely with international teams.

Agent Sandboxing and Isolation: Implement and maintain secure, isolated execution environments for autonomous agents using Firecracker MicroVMs or restricted Kubernetes and Docker configurations. Secure Data Infrastructure: Provision, optimize, and scale a multi-layered data architecture, including PostgreSQL for transactional workloads, ChromaDB or PGVector for vector storage, and Neo4j for graph-based knowledge mapping. Event-Driven Orchestration: Build and manage high-performance event streams using AWS SQS, EventBridge, or Kafka to support agent-to-agent communication and human-in-the-loop escalation workflows. Infrastructure as Code: Automate the provisioning, configuration, and management of AWS infrastructure and Kubernetes clusters using industry-standard IaC practices. Security and Identity Management: Integrate identity providers and B2B identity solutions, including WorkOS, to support secure authentication, multi-tenancy, and strict separation of tenant data and configurations. Network Security and Egress Controls: Design and enforce egress firewalls, proxy-only outbound routing, and other safeguards to prevent autonomous agents from exposing or exfiltrating sensitive data. Secure CI/CD Pipelines: Implement automated security checks and controls throughout the software delivery lifecycle to strengthen infrastructure security and deployment reliability. Workflow Management: Support reliable execution of long-running, multi-stage agent workflows through orchestration technologies such as Temporal. Compliance and Observability: Help prepare infrastructure for security and privacy standards while improving agent workload monitoring, tracing, and operational visibility. Requirements: Cloud and Container Security: Extensive hands-on experience with AWS, Kubernetes, and container security. Practical experience with Firecracker MicroVMs is highly desirable. Database Expertise: Experience managing and scaling vector databases such as ChromaDB and PGVector, as well as graph databases used in AI applications. Security-First Mindset: Strong understanding of zero-trust architecture, OWASP principles, secure infrastructure design, and the security challenges associated with AI systems. Event-Driven Architecture: Proficiency in messaging systems, event streaming, and real-time data processing technologies such as AWS SQS, EventBridge, or Kafka. Infrastructure Automation: Advanced scripting skills in Python and Bash, alongside a proven track record of implementing infrastructure automation and security gates in CI/CD pipelines. Workflow Orchestration: Experience with Temporal or similar technologies for managing complex, long-running, multi-stage workflows. Identity and Multi-Tenancy: Familiarity with identity providers, B2B authentication, tenant isolation, and secure access management. Compliance Knowledge: Experience preparing infrastructure for SOC 2, ISO 27001, or GDPR compliance readiness is an advantage. AI Observability: Familiarity with tools such as LangSmith or Langfuse for tracing, monitoring, and observing AI agent workloads is desirable. Collaboration and Ownership: Ability to work independently on complex security challenges, collaborate effectively across engineering teams, and maintain a proactive approach to infrastructure reliability and risk reduction. Benefits: Comprehensive Healthcare: Company-paid medical insurance and programs supporting mental and physical well-being. Mental Health Support: Access to mental health programs and resources. Sick Leave: Five additional sick-leave days per year. Paid Vacation: 20 working days of paid annual vacation, in addition to local public holidays. Fully Remote Work: 100% remote working arrangements. Learning and Development: Access to internal meetups, conferences, workshops, a Udemy license, language courses, and company-paid certifications. Professional Growth: Opportunities to learn from a global community of experienced professionals and expand technical expertise. Internal Mobility: Access to an internal mobility program that supports transitions between projects to encourage career development and professional growth. International Projects: Opportunities to contribute to large-scale technology initiatives with international and fast-growing clients. Collaborative Culture: A welcoming work environment that promotes teamwork, open communication, knowledge sharing, and regular team-building activities. Long-Term Employment: The opportunity to build a lasting career while working with modern cloud, security, and AI technologies.