Interpret

Systems Engineer

• Design, build, and maintain internal and participant-facing tools, dashboards, portals, automations, and workflow systems that support recruiting, screening, fielding, project coordination, reporting, and operational visibility.
• Translate research and business needs into clear requirements, prototypes, production-ready tools, and ongoing product improvements.
• Replace manual work with scalable systems that improve speed, accuracy, consistency, data quality, and user experience.
• Balance speed, quality, cost, supportability, and long-term maintainability when choosing SaaS-native automation, AI-assisted development, or custom development.
• Build and govern AI agent workflows that help automate coding, research operations, task routing, data handling, documentation, and project coordination.
• Design, configure, or evaluate MCP servers and clients that connect AI tools to approved APIs, SaaS systems, data resources, and internal workflows.
• Use AI-assisted development platforms such as Codex, Claude Code, Cursor, GitHub Copilot, Lovable, Base44, or comparable tools while validating generated code, dependencies, architecture, and security assumptions.
• Define practical guardrails for agent behavior, tool access, human approval points, logging, error handling, retries, rollback paths, and responsible use of sensitive data.
• Build and support integrations across survey platforms, CRM systems, project management tools, reporting tools, databases, cloud services, and other business systems.
• Work with REST APIs, webhooks, OAuth/OIDC, JSON payloads, schema validation, data mapping, sync jobs, ETL-style workflows, error handling, retries, and auditability.
• Design data workflows that support cleaner handoffs, better reporting, fewer manual steps, clear data lineage, and secure access to operational and participant information.
• Evaluate third-party SaaS tools, connectors, MCP servers, APIs, and automation platforms for fit, cost, permissions, reliability, and supportability.
• Review, QA, refactor, and maintain production tools, including AI-generated code, before and after launch.
• Use version control, centralized documentation, release notes, testing, monitoring, logging, and change tracking to keep systems reliable and understandable.
• Apply practical privacy and security practices for PII and sensitive business data, including least privilege, permissions, credential handling, secure configuration, and data retention awareness.
• Communicate status, risks, tradeoffs, training needs, and implementation decisions clearly to technical and non-technical stakeholders.

Senior Systems Developer