Position Summary:

This role is for a product engineering leader who will lead Japan Core Insurance Systems (CIS) delivery from MGCC, India, and drive a broad Quality Engineering and QA automation transformation. The leader is expected to be AI-first in engineering practice: shaping the Agentic Development Lifecycle (ADLC), embedding AI and automation into SDLC/ADLC workflows, and building or contributing to agentic platforms, engineering agents, testing agents, and reusable accelerators that improve speed, quality, predictability, and developer experience.

Role positioning: Insurance, policy administration, or PAS exposure is useful but optional. The primary requirement is proven product engineering leadership with hands-on, AI-first transformation across engineering and quality.

Scope & Business Impact:

- Lead Japan CIS delivery, operational stability, quality outcomes, and financial governance from MGCC, India.
- Drive AI-first engineering practices across delivery, quality engineering, release readiness, and production stability.
- Lead the QA automation and Quality Engineering transformation for Japan technology deliverables.
- Establish agentic SDLC/ADLC patterns that improve developer productivity, test effectiveness, defect prevention, and delivery predictability.
- Partner with Japan technology leaders, product owners, architecture, operations, risk, and vendors to deliver measurable business and engineering outcomes.
- Enable faster change, stronger engineering discipline, improved quality, operational resilience, and transparent delivery economics.

Key Responsibilities: Product Engineering Leadership for CIS

- Provide end-to-end technology leadership for Japan CIS, including delivery, engineering discipline, operational stability, security, risk management, and financial outcomes.
- Operate as a product engineering leader, balancing business priorities, platform reliability, technical debt reduction, engineering standards, and delivery accountability.
- Partner with Japan stakeholders to shape roadmaps, define measurable outcomes, and ensure India delivery is aligned to Japan portfolio priorities.
- Drive up-to-date engineering practices such as API enablement, modularization, data modernization, observability, DevSecOps, and engineering governance where relevant to platform evolution.

AI-First SDLC / ADLC Transformation

- Lead adoption of the Agentic Development Lifecycle (ADLC), embedding AI and automation into requirements analysis, design, coding, code review, test generation,



defect triage, release readiness, documentation, and production support workflows.
- Actively contribute to ADLC practices by helping define patterns, reusable assets, guardrails, metrics, and adoption playbooks for AI-assisted engineering.
- Sponsor and/or directly contribute to agentic platform capabilities, including engineering agents, testing agents, quality agents, knowledge agents, and workflow orchestration that support SDLC/ADLC use cases.
- Ensure AI adoption is governed, secure, measurable, and practical for engineers, with clear controls for quality, risk, data handling, and human oversight.
- Measure impact through cycle-time improvement, automation coverage, defect leakage reduction, quality signals, engineering productivity, reuse, and adoption maturity.

Quality Engineering & QA Automation Transformation

- Own QA and Quality Engineering strategy for Japan technology deliverables, moving from manual, phase-based testing to automation-first and AI-assisted continuous quality engineering.
- Embed automated testing, test data practices, regression optimization, service virtualization, shift-left quality, and quality gates into Agile and CI/CD delivery models.
- Use AI and intelligent automation for test design, test-case generation, impact analysis, regression selection, defect prediction, test coverage insights, and quality reporting.
- Establish common QA platforms, metrics, standards, and governance across portfolios while improving speed, stability, and production quality.

Financial, Vendor & Delivery Governance

- Own and manage technology budgets for Japan platforms delivered from MGCC, India, including planning, forecasting, cost transparency, and value realization.
- Govern strategic partners and vendors to align with product engineering, automation-first delivery, AI-enabled quality, and measurable outcome commitments.
- Strengthen operating cadence, portfolio transparency, dependency management, risk mitigation, and stakeholder communication across India and Japan teams.

Talent & Capability Building

- Build strong product engineering, quality engineering,



automation, AI engineering, and platform capability within the India team.
- Upskill teams toward AI-first engineering roles, including prompt patterns, agentic workflows, test automation craftsmanship, engineering discipline, and secure use of AI tools.
- Develop leadership depth, succession, and communities of practice across engineering, QA automation, and ADLC adoption.

Knowledge Skills & Experience:

- 15+ years of technology leadership experience with ownership of large engineering teams, complex platforms, delivery outcomes, financial governance, and senior stakeholder management.
- Strong product engineering mindset with experience improving engineering standards, platform reliability, delivery predictability, and developer experience.
- Demonstrated experience driving AI-first engineering transformation across SDLC or ADLC practices.
- Hands-on or sponsorship experience with Agentic AI for engineering, including agentic platforms, SDLC/ADLC agents, automation accelerators, workflow orchestration, and engineering productivity use cases.
- Proven experience leading enterprise-scale QA / Quality Engineering transformation, including automation strategy, CI/CD integration, test architecture, metrics, and governance.
- Experience with modern engineering practices such as cloud-aligned modernization, APIs, DevSecOps, observability, data modernization, platform engineering, and engineering controls.
- Strong financial discipline, vendor governance, operational risk awareness, and ability to connect technology investment to business value.
- Experience working with Japan, Asia, or other cross-border stakeholders is strongly preferred.
- Insurance, policy administration, PAS, agent commission, or financial-services platform experience is beneficial but optional; it is not a mandatory prerequisite for this role.

Personal Characteristics:

- AI-first, engineering-led transformation leader with a pragmatic delivery mindset.
- Hands-on enough to shape platforms, patterns, and agentic engineering practices, while senior enough to lead strategy, governance, and stakeholder alignment.
- Balances innovation with controls, security, quality, operational resilience, and financial discipline.
- Collaborative, culturally aware, outcome-driven, and comfortable working across India and Japan leadership teams.
- Strong people leader who can build confidence, capability, and adoption across engineering and QA teams.

📌 Product Engineering Leader (Pune)
🏢 MetLife
📍 Pune