Senior Systems Developer

Senior Systems Developer

As a Senior Systems Developer, you will design, build, implement, and maintain SaaS tools, APIs, MCP-connected agents, automations, and data workflows that improve the primary research process across Interpret and the Good Entertainment Group. This role supports both internal operations and participant-facing experiences, with a focus on tools that help teams recruit, screen, field, manage, track, and report research more effectively.

This is a senior individual contributor role for someone who can move from idea to prototype to reliable production system. You will partner with stakeholders to understand operational pain points, design durable solutions, review and harden AI-generated code, and maintain systems responsibly over time.

The right person is a builder who understands SaaS platforms, API design, databases, AI-assisted development, Model Context Protocol, and agent workflows, and can make complex technology useful for research teams and participants.

At Interpret, we consider ourselves fun scientists, and we're searching for someone who holds a common love for the industries we work in, has a curiosity for consumer behavior, and wants to apply their analytic chops and methodological expertise to the video game space. A fun scientist is someone who thrives in a dynamic environment where your hobbies and personal passion for gaming make work feel like, well, not work.

Responsibilities

• 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.

AI Agents, MCP & AI-Assisted 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.

Integrations, APIs, SaaS Tooling & Data Workflows

• 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.

QA, Documentation & System Responsibility

• 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.

Skills

• Senior-level ability to build SaaS tools, internal applications, automation layers, APIs, dashboards, and participant-facing systems.
• Strong working knowledge of APIs, webhooks, OAuth/OIDC, JSON, data mapping, SQL or structured data, and SaaS integration patterns.
• Hands-on knowledge of MCP concepts, MCP servers and clients, AI agents, tool-calling workflows, and AI-assisted development.
• Experience with AI coding platforms such as Codex, Claude Code, Cursor, GitHub Copilot, Lovable, Base44, or comparable tools.
• Practical understanding of databases, cloud-hosted applications, GitHub or version control, QA, release management, logging, monitoring, and post-launch support.
• Sound judgment around privacy, PII, permissions, access control, credentials, vendor tools, and responsible AI use.
• Ability to turn stakeholder needs into useful, maintainable systems and explain technical concepts clearly.

Qualifications:

• 4 to 7+ years of relevant experience in systems development, SaaS tools, automation engineering, business systems, technical operations, software development, or a related field.
• Demonstrated experience building and maintaining production tools, integrations, dashboards, automations, internal applications, or participant-facing systems.
• Experience with APIs, authentication, data handling, SaaS platforms, databases, version control, and sensitive operational or participant data.
• Direct MCP knowledge or hands-on experience with MCP servers and clients, AI agents, internal copilots, tool-calling workflows, or LLM-connected systems is strongly preferred.
• Experience using AI coding tools or rapid application platforms such as Codex, Claude Code, Cursor, GitHub Copilot, Lovable, Base44, or similar tools.
• Experience supporting QA, documentation, release readiness, stakeholder training, and ongoing product maintenance.
• Bachelor's degree in a relevant field is preferred, but equivalent professional experience will be considered.
• Must be authorized to work in the United States.

Preferred experience:

• Experience in market research, insights, operations, gaming, entertainment, SaaS, AI systems, or technology environments.
• Familiarity with qualitative recruiting, quantitative fielding, participant communities, screening workflows, and primary research operations.
• Experience designing tools, portals, integrations, or automations that support research teams or participant-facing experiences.
• Familiarity with practical privacy and security controls, access reviews, audit logs, vendor risk, data retention, and responsible AI guardrails.

Compensation + Benefits

The pay range for this position at the start of employment is expected to be between $109,000 - $155,000 per year, is based on market location, and may vary further depending on individualized factors, such as job-related knowledge, skills, experience, and other objective business considerations. In addition to the base salary, total compensation also includes tiered performance bonus, health/dental/vision, 401(k), generous paid time off, physical & mental wellness program, paid parental/family leave, and continuing education scholarship program.