Senior Software Engineer

Position Overview

Matrix Education is developing an in-house product capability to expand its reach beyond traditional classrooms. We are forming a dedicated product team responsible for building and delivering software directly used by students, parents, and teachers. This important position forms a key foundational role as we grow the team.

Reporting to the Head of Technology and collaborating closely with the Head of Digital Product and the wider Product Team, you will develop and deploy applications using Next.js, TypeScript, Node.js, and PostgreSQL. Integration with Salesforce and Snowflake will be achieved via a common business API layer. Our primary development environment is Claude Code, and candidates are expected to bring proficient, autonomous development skills from day one. You will architect and manage an AI-centric development pipeline featuring full automation, CI/CD, preview environments, automated validations, and safety mechanisms to enable rapid, safe autonomous agent-driven workflows.

Key Responsibilities

• Develop and launch software products as a member of a small team.
• Create full-stack applications using Next.js and Node.js, handling server components and APIs through production, primarily using Claude Code and Cursor.
• Engage in initial problem framing, story mapping, and scope definition rather than working from finalized specs, advocating for scope adjustments based on engineering impact.
• Integrate with enterprise platforms such as Salesforce and Snowflake through a shared business API to ensure logic reuse across applications.
• Oversee review processes of agent-generated code: identify issues, determine what to keep, modify, or return with better context.
• Deliver at least one customer-facing release within your first three months that directly benefits students, parents, or teachers.
• Design and enhance an end-to-end autonomous agent-driven development lifecycle, including test automation, branch management, and CI/CD processes that maintain human oversight at key points.
• Build monitoring and observability tools to track agent operations, testing outcomes, and production deployments for continuous performance improvement.
• Implement security guardrails using OWASP guidelines for LLM applications to ensure safe user-facing interactions.
• Define and track product outcomes with dashboards monitoring engagement and conversion metrics, influencing product decisions by factoring feasibility and cost implications.
• Develop reusable components and shared patterns to avoid redundant integration efforts across product teams.

Experience and Qualifications

• Proven experience deploying Next.js and TypeScript applications with both client and server-side rendering in production environments.
• At least five years of professional software development experience, including a minimum of one year using AI agents for substantial parts of the workflow.
• Strong expertise in Node.js, RESTful API design, and integration with third-party SaaS systems often inconsistent with documentation.
• Proficiency with SQL and PostgreSQL at production scale.
• Experience designing and scaling AI-first or highly automated CI/CD pipelines and agent-driven development workflows.
• Ability to influence product decisions based on deep technical insight and understanding of code implications.

AI Fluency and Developer Mindset

• Daily usage of advanced AI development tools like Claude Code or Cursor, with critical perspectives on prompt efficiency.
• Capability to distinguish correct, reliable code from superficially plausible but faulty code, maintaining a high standard before release.
• Active engagement in shaping the future of agentic engineering and insights on optimizing small team dynamics.
• Proactive experimentation, transparent knowledge sharing, and frequent delivery of incremental improvements without strict instructions.

Skills and Personal Attributes

• Strong intuitive understanding of user-centric product value focused on students and parents beyond mere functionality.
• Comfort with discovery and problem framing by engaging directly with end users and analyzing funnel data.
• High accountability for individual work, early identification of blockers, and proactive ownership of build stability.
• Pragmatic approach to tooling, favoring the simplest, safest method whether deterministic or agentic.
• Clear and concise written communication for effective interaction with AI agents, team members, and other stakeholders.
• Honest and reflective about knowledge gaps and areas for growth.

Preferred Qualifications

• Familiarity with Salesforce and Snowflake data structures.
• Understanding of the MCP pattern for connecting agents to tools.
• Experience with observability solutions for tracing AI agent executions, such as LangSmith or Langfuse.
• Background in educational technology or consumer products aimed at students.

Success Criteria

Within 90 Days

• Deliver a customer-facing or significant internal release using the agentic development workflow with documented agent output decisions.
• Present an evaluation and roadmap for the agentic engineering lifecycle and automated delivery process to leadership with initial implementation live.
• Manage production deployments independently including monitoring, troubleshooting, and rollback.
• Contribute directly to story mapping and alter project scope based on findings.

Within 6 to 12 Months

• Complete multiple product releases including ownership of a customer-facing product from initial conception through performance measurement.
• Establish a robust agentic development lifecycle with rapid feature delivery supported by automated safety mechanisms.
• Operate live outcome dashboards with iterative improvements based on data insights.
• Create reusable components and shared patterns widely adopted by the development team.