Product Engineering Leader

Metlife; Pune District; On-site; INR 4,000,000 - 7,500,000; Full time

Job summary

MetLife is seeking a product engineering leader to drive CIS delivery from MGCC, India, with an AI-first transformation across engineering and QA. You will shape the Agentic Development Lifecycle, embed AI into SDLC workflows, and lead agentic platforms, ensuring speed, quality, and predictable delivery for Japan CIS.

You will partner with Japan technology leaders to define roadmaps, govern budgets, and elevate engineering standards while building capability within the India team and promoting

Qualifications

• 15+ years of technology leadership across large engineering teams and complex platforms.
• Proven product engineering mindset with focus on reliability and delivery predictability.
• Experience driving AI-first transformation across SDLC/ADLC practices.
• Hands-on or sponsorship experience with agentic AI for engineering and automation accelerators.
• Proven enterprise-scale QA/Quality Engineering transformation experience including automation strategy.

Responsibilities

• Provide end-to-end technology leadership for CIS delivery, ensuring operational stability, security, risk management, and financial outcomes.
• Lead the QA automation and Quality Engineering transformation for Japan technology deliverables.
• Drive modern engineering practices: API enablement, modularization, observability, DevSecOps and governance.
• Champion ADLC adoption, define patterns, reusable assets, and adoption playbooks for AI-assisted engineering.
• Build capability within the India team, upskill for AI-first engineering roles, and foster communities of practice across teams.
• Govern budgets, vendor relationships, and cross-border collaboration with Japan stakeholders to deliver measurable outcomes.

Skills

Technology leadership

Product engineering

AI-first transformation

QA automation

Cross-border collaboration

Vendor governance

Job description

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 modern 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.
• 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.