• Development of scalable, high-performance solutions • Collaboration with the Technology team • Contribute to product improvement initiatives

• Design, implement and maintain robust integrations between Censys Platform and third-party SOAR, SIEM, TIPs solutions • Develop and operate scalable, high-availability API connectors • Maintain and improve existing Censys open source APIs • Write and maintain internal pipelines and IaC to manage the deployment of new and existing Censys-hosted integrations and services • Design automated solutions for building, testing, monitoring, and deploying applications in a continuous integration environment • Maintain a strong customer focus, prioritizing customer feature requests and helping define the integrations roadmap • Stay current on emerging SOAR, SIEM, and TIP technologies to guide integration strategy

• Co-own architecture for APIs, data pipelines, multi-tenant controls, time-sync, and analytics; and write reference designs. • Design & build scalable REST/GraphQL and event-driven services supporting diverse integration patterns. • Develop high-volume, real-time pipelines with robust validation, error handling, pass-through, and observability. • Engineer for ATO from day one, aligning designs with NIST 800-53, DoD IL, and FedRAMP; contribute evidence for accreditation. • Evolve our API Developer Hub (design, docs, testing, lifecycle tooling) and self-service partner onboarding workflows. • Implement API lifecycle management (versioning, deprecation, migration) and platform analytics for internal/external users. • Onboard third-party models and simulations (including AI/ML/LLM and space-ops training software) with clear methodology and tooling. • Collaborate cross-functionally with Product, Security, DevOps, QA, and external partner teams; engage with government stakeholders. • Mentor engineers on integration patterns, reliability, and operational excellence; balance speed with long-term platform health.

• Work across multiple projects to improve LLM performance on code tasks. • Lead end-to-end delivery of AI agent use cases (e.g., coding copilots, creative assistants). • Evaluate and review model-generated code for accuracy, maintainability, and performance. • Analyse and provide structured, written rationales for code quality and rankings. • Collaborate with the client´s teams to identify edge cases and improve model behaviour.