Teams at Money Forward, Inc.

Design, develop, and operate scalable cloud-native systems using Go, concurrency, distributed systems, REST APIs, microservices, SQL, AWS, Docker, and Kubernetes. Lead releases, CI/CD, testing, troubleshooting, observability, and production improvements. Use and govern AI-assisted development tools, review AI-generated outputs, mentor engineers, improve team workflows, and collaborate with Product, QA, DevOps, and operational stakeholders.

Lead the design and delivery of AI context engineering and evaluation harness workstreams. Develop RAG, memory, token-management, ontology, MCP integration, sandboxing, orchestration, validation, and evaluation standards. Support pilot teams, define integrations with GitHub, Notion, and Slack, build YAML-based knowledge models and repo-native harness prototypes, and translate pilot evidence into company-wide best practices and technical standards.

Lead the design and implementation of agentic application-security workflows across the SDLC. Build AI agents for threat modeling, secure coding, CI/CD validation, testing, release risk assessment, and production feedback. Define security context models, guardrails, decision rules, human-review requirements, and escalation paths. Integrate workflows with engineering platforms, lead engineers across teams, validate outputs with security experts, and continuously improve agent quality, observability, and production readiness.