Senior Product Engineering Leader

Job description

Calling all innovators – find your future at Fiserv. We’re Fiserv, a global leader in Fintech and payments, and we move money and information in a way that moves the world. We connect financial institutions, corporations, merchants, and consumers to one another millions of times a day – quickly, reliably, and securely. Any time you swipe your credit card, pay through a mobile app, or withdraw money from the bank, we’re involved. If you want to make an impact on a global scale, come make a difference at Fiserv. Job Title Senior Product Engineering Leader Job Location - Mumbai, Noida, Pune, Bengaluru or Chennai About your role: As a Senior Product Engineering Leader, you will own the engineering velocity, product delivery systems, and AI-enabled development practices that enable Fiserv product teams to ship faster, with higher quality, and with greater business impact. You will be the connective tissue between product leadership, P&L owners, and engineering execution — translating business outcomes into delivery systems, reducing friction from idea to production, and raising the engineering bar across the organization. You will operate at the intersection of product strategy and engineering excellence: accelerating feature throughput, embedding AI into the software delivery lifecycle (SDLC), and ensuring teams are measuring what matters — from cycle time to customer-facing business outcomes. While you will also strengthen the release governance, CI/CD, and operational readiness practices that protect production reliability in a regulated fintech environment, your primary mandate is product velocity and delivery excellence, not infrastructure operations. What you'll do: Product Velocity and Engineering Delivery Partner closely with P&L leaders, product managers, and business stakeholders to understand roadmap priorities, translate them into engineering delivery commitments, and hold teams accountable to shipping outcomes — not just activity Define and drive product engineering KPIs including cycle time, lead time, deployment frequency, feature throughput, and customer-facing quality metrics across product lines Identify and systematically remove delivery bottlenecks — whether in planning, dependency management, testing throughput, review cycles, or release coordination — that slow feature flow from backlog to production Establish clear, lightweight delivery governance: sprint health reviews, milestone tracking, release readiness gates, and executive-level visibility into what is shipping, when, and with what risk Build and sustain a culture of delivery accountability across engineering teams — where commitments are made carefully, tracked rigorously, and missed commitments generate learning, not blame Drive reduction of technical debt and legacy complexity that impairs product velocity — prioritizing modernization efforts based on delivery impact and business value AI-Enabled SDLC and Developer Productivity Lead the adoption of AI-assisted development practices across engineering teams — including AI code generation, AI-driven test authoring, intelligent code review, and automated documentation — to measurably accelerate developer throughput Build or acquire an AI-enabled SDLC platform: integrating tools such as GitHub Copilot, Cursor, Amazon CodeWhisperer, or equivalent into standardized workflows, measuring productivity lift, and scaling adoption across teams Define and track Developer Experience (DX) metrics — build times, local feedback loops, onboarding speed, context-switching cost — and drive continuous improvement Champion agentic AI workflows for repetitive engineering tasks: test generation, regression analysis, release notes, incident summarization, and compliance evidence collection Evaluate and pilot emerging AI engineering tools; build a learning community and internal capability so engineering teams stay ahead of the curve on AI-enabled productivity Partner with platform engineering to ensure the AI developer toolchain is secure, compliant with data classification standards, and accessible across distributed teams Collaboration with Product and P&L Leaders Act as the primary engineering partner for product and P&L leaders — present in roadmap planning, sprint reviews, quarterly business reviews, and investment decisions Translate business objectives into engineering investment priorities: make transparent trade-offs between feature delivery speed, technical debt reduction, reliability investment, and AI tooling adoption Build shared accountability between product and engineering by co-owning delivery metrics, release milestones, and customer-outcome targets — not just engineering-internal health metrics Provide P&L leaders with honest, data-driven signals on engineering capacity, velocity trends, and delivery risk — enabling better prioritization and resource allocation decisions Represent the engineering perspective in product and business planning forums; challenge scope, timeline, and quality assumptions with data and engineering judgment CI/CD, Release Excellence, and Operational Readiness Design and implement CI/CD standards for microservices, data pipelines, core banking integrations, API platforms, and infrastructure changes — focused on reducing release cycle time and increasing deployment confidence Build automated quality gates for unit, integration, contract, security, performance, regression, and compliance checks — embedded in the delivery pipeline, not bolted on at the end Define release patterns including blue-green deployments, canary releases, feature flags, progressive rollout, and automated rollback — enabling teams to ship frequently with reduced blast radius Establish measurable controls for deployment consistency, release evidence, segregation of duties, audit trails, and change management in regulated delivery environments Partner with SRE and platform engineering on observability, SLOs, error budgets, incident response, operational readiness gates, and toil reduction — ensuring engineering teams own their production health Drive adoption of common release patterns, automated checks, and operational readiness practices across high-priority engineering teams Responsibilities listed are not intended to be all-inclusive and may be modified as necessary. Experience you'll need to have: 15+ years of progressive software engineering experience, with at least 5 years in a senior engineering leadership role owning product delivery outcomes, not just infrastructure or tooling 10+ years of demonstrated experience partnering directly with product management and P&L leaders — including joint roadmap ownership, shared delivery metrics, and executive-level reporting on engineering velocity and quality 8+ years of hands-on experience designing and scaling CI/CD pipelines, deployment automation, release controls, and production readiness practices for distributed systems at significant product scale 8+ years of experience operating in product engineering contexts — including sprint planning, feature delivery, cross-functional dependency management, and launch coordination — not solely SRE or platform engineering 5+ years of experience implementing and scaling AI-assisted development tools (GitHub Copilot, Cursor, AI code review, AI test generation, or equivalent) across engineering organizations, with measurable productivity outcomes 5+ years of experience defining and tracking engineering productivity and delivery metrics — cycle time, deployment frequency, change failure rate, lead time, feature throughput — and driving measurable improvement 5+ years of experience implementing release evidence, segregation of duties, audit trails, and change controls in regulated or operationally critical environments Demonstrated ability to build and sustain high-trust relationships with non-engineering business stakeholders — making engineering trade-offs legible and participating actively in investment and prioritization decisio