Lead AI Engineer (Chennai / Pune)

• Join Money Forward at a major strategic turning point as the company shifts from “cloud” to “AI” and advances AX (AI Transformation) beyond traditional DX.
  
• Help build the foundation for AI agents and “digital workers” that can autonomously perform back-office tasks across Money Forward products.
  
• Own greenfield architecture for agentic security workflows that directly support the company’s AI strategy, product trust, and secure AI-driven development.
  
• Work on a rare intersection of agentic AI, application security, and cross-team engineering leadership, shaping reusable standards, guardrails, and implementation patterns across product teams.
  
• Contribute to Money Forward’s ambition to become Japan’s No. 1 back-office AI company by enabling safer, faster, and more reliable AI-powered value creation.
  
• Help shape one of the company’s most advanced agentic AI initiatives: a multi-agent security workflow designed to support the full software development lifecycle, while keeping human review, safety boundaries, and release governance in place.
  

• Design end-to-end agentic security workflows for SDLC validation, patch management, proactive testing, risk reporting, and release gates.
  
• Own the product security context model, including architecture, data sensitivity, authentication/RBAC, credential and PII handling, logging touchpoints, release tier, and critical product flows.
  
• Define agent decision rules, including advisory behavior, human-review requirements, release-blocking criteria, risk thresholds, and escalation paths.
  
• Design and implement agent guardrails such as least-privilege access, prompt-injection handling, safe tool execution, audit logging, rollback, and kill-switch mechanisms.
  
• Build and maintain AI agent workflows using LLMs, context engineering, tool integrations, orchestration, harness design, loop engineering, and evaluation pipelines.
  
• Validate agent outputs with security experts before rules are trusted for production use.
  
• Lead application engineers across divisions and translate agentic workflow designs into stack-specific implementation patterns.
  
• Work with SRE/PRE on CI/CD integration, GitHub/CircleCI workflows, Datadog checks, staging safeguards, and release-gate mechanics.
  
• Coordinate with QA, privacy, and security specialists on regression validation, release readiness, PII handling, and secure coding rules.
  
• Own false-positive tuning, rule-change backlog, and continuous improvement of agent quality.
  

Requirements