Senior Principal Engineering Leader

Fiserv•Remote, Arizona, AZ

5d•Remote

About The Position

As a Senior Principal Engineering Leader, you will lead the technical direction for highly available platform and infrastructure modernization across critical engineering domains. You will work with engineering, architecture, product, security, and site reliability engineering teams to solve complex distributed systems challenges, improve platform resilience, and guide production-safe modernization efforts. You will also help shape how AI is applied within engineering workflows and platform capabilities, with a focus on measurable impact, responsible implementation, and scalable adoption across multiple teams.

Requirements

12+ years of experience in engineering delivery, software engineering, platform engineering, or distributed systems engineering, including architecting and delivering highly available production platforms
12+ years of experience designing and building distributed services using Java, Go, or similar object-oriented or compiled programming languages
10+ years of experience with API platform engineering, service-oriented architectures, or platform infrastructure in large-scale environments
10+ years of experience leading legacy modernization or microservices transformation initiatives using phased migration approaches in production systems
8+ years of experience with service mesh and proxy technologies such as Istio, Envoy, or equivalent technologies
8+ years of experience with infrastructure-as-code practices using Terraform or equivalent technologies in cloud or hybrid environments
8+ years of experience influencing architecture standards, design reviews, or engineering best practices across multiple teams
3+ years of experience evaluating, integrating, or implementing AI, machine learning, or generative AI capabilities in software engineering, platform engineering, or operational workflows
3+ years of experience defining technical requirements, controls, or implementation patterns for AI-enabled solutions, including model integration, application performance, or data usage considerations
Bachelor's degree or higher in computer science, computer engineering, information technology, or a related field, or an equivalent combination of education, related experience and/or military experience

Nice To Haves

Experience in financial services, payments, or other transaction-intensive platforms
Experience supporting platforms serving 100M+ users or similarly large-scale distributed environments
Experience with observability, resilience engineering, and fault-tolerant system design
Experience with AI-assisted developer tools, intelligent automation, or model-enabled platform capabilities

Responsibilities

Lead the technical direction and engineering delivery for platform modernization initiatives, including migration from legacy architectures to microservices-based systems in high-availability production environments
Design and evolve API gateway patterns, service mesh capabilities, and distributed service architectures that support secure, scalable, and resilient platforms
Drive architecture decisions for complex engineering problems involving reliability, scalability, latency, migration risk, and operational continuity
Establish engineering patterns, reference designs, and technical standards that improve consistency and delivery quality across multiple teams
Guide and deliver phased, zero-downtime migration strategies that reduce production risk while improving platform maintainability and speed of change
Partner with product, infrastructure, security, and site reliability engineering teams to align and delivery on technical solutions with business priorities, operational requirements, and risk controls
Identify, evaluate, and guide the adoption of AI and machine learning capabilities within engineering platforms, development workflows, or operational processes based on measurable business and technical outcomes
Define technical patterns and guardrails for responsible use of AI in software engineering, including model integration, data handling, observability, performance monitoring, and risk management
Influence large cross-functional initiatives through architecture reviews, design guidance, and hands-on technical leadership
Mentor senior engineers through design reviews, engineering best practices, and technical problem solving