1 day ago
Responsibilities
- Define enterprise architecture and technical strategy for agentic software engineering capabilities.
- Establish reference architectures for coding agents, harnesses, reusable libraries, and automated development workflows.
- Set standards for Model Context Protocol servers, tools, interfaces, and lifecycle management.
- Guide design decisions involving security, scalability, reliability, and platform interoperability.
- Establish controls for evaluating, testing, monitoring, and governing AI-generated software.
- Optimize complex software architectures for changing requirements and enterprise-scale adoption.
- Advise engineering, product, implementation, and client-facing teams on high-impact technical decisions.
- Lead investigation and resolution of complex software and integration challenges.
- Coach senior engineers and technical leads on architecture, agentic programming, and engineering excellence.
- Influence long-term roadmaps, development practices, and technology investments.
Requirements
- Master-level expertise in software architecture, platform engineering, and enterprise application development.
- Advanced proficiency with Python, TypeScript, or comparable languages used for complex software platforms.
- Demonstrated success shaping technical strategy for large-scale, long-term software initiatives.
- Deep experience with distributed systems, cloud architecture, APIs, security, and production reliability.
- Proven ability to establish engineering standards and influence decisions across organizational boundaries.
- Expertise in code quality, automated testing, performance optimization, and software lifecycle governance.
- Bachelor-level degree in computer science, engineering, or a related field, or equivalent practical experience.
- Preferred: expertise in agentic programming, coding agents, or large language model application architecture.
- Preferred: experience with Model Context Protocol development and adoption patterns.
- Preferred: knowledge of Claude Code, GitHub Copilot, OpenCode, or comparable AI engineering ecosystems.
- Preferred: experience establishing AI evaluation, observability, safety, and governance frameworks.
- Preferred: client-facing engineering experience involving technical strategy, implementation, and executive-level communication.
- Preferred: advanced degree in computer science, engineering, or a related technical discipline.
Benefits
- Full-time employment.
- Competitive salary and benefits.
- Personal and professional learning opportunities.
- Inclusive and diverse work environment.
- Resources and opportunities to give back to the community.
- Opportunity to make an impact in fintech.
Tech Stack
Categories
About FIS
FIS builds financial technology for banks, merchants, and capital-markets firms, including core banking platforms, payment processing, fraud/risk tools, and investment/treasury systems. It sells enterprise software, cloud services, and outsourced processing via long-term contracts and transaction-based fees. Founded in 1968 and headquartered in Jacksonville, Florida, FIS is a Fortune 500 public company trading on the NYSE (FIS) with customers worldwide.