Principal Solution Architect, Platform Engineering

FIS Global • Jacksonville, FL

5d

About The Position

The Principal Solution Architect reports to the Head of Architecture for Platform Engineering and designs, documents, and drives adoption of enterprise platform capabilities. Platform Engineering provides shared capabilities that help product engineering teams deliver secure, reliable, performant, high-quality products to clients faster. Its portfolio includes AI Engineering, API & Event Management, Front End, Site Reliability Engineering (SRE), Developer Experience & Quality, and Customer Identity & Access Management.

The role primarily focuses on AI Engineering: architecting how AI and agentic capabilities are incorporated into the software development lifecycle (SDLC), enabling engineering teams to deliver higher-quality software faster and more safely. The architect shapes patterns, platforms, and guardrails to scale governed, agent-driven workflows, while also contributing across platform domains and potentially leading initiatives beyond AI.

The role spans the full SDLC, from AI-assisted planning, design, and coding through automated review, testing, security remediation, release, and operations. It also covers governance, security, and measurement needed to use these capabilities responsibly at enterprise scale. The architect applies hands-on software engineering experience, cloud-native and AI-native patterns, enterprise architecture practices, and vendor evaluation to translate business needs into practical solutions and roadmaps for modernization.

The position partners with platform leaders, owners, product partners, and stakeholders to shape platform capabilities and technology direction. It includes validating designs through proofs of concept and reference implementations, contributing to architecture reviews and governance, and communicating the business value, options, and trade-offs of the architectural roadmap.

Requirements

• 10+ years of solution architecture and senior software engineering experience, including significant hands-on product delivery in a fast-paced, global software delivery organization operating with ambiguity.
• Expert understanding of software and internet architecture, including modern front-end and back-end stacks, API management, identity and access management, cloud-native and on-premises infrastructure, containers, Kubernetes, infrastructure as code, networking, internet connectivity, and browser and mobile application delivery.
• Deep expertise designing and delivering AI-enabled engineering capabilities, including AI coding assistants and agents, LLM application patterns such as retrieval-augmented generation, tool use and multi-agent orchestration, context engineering, and model and agent quality evaluation; hands-on experience applying them to software delivery workflows.
• Strong understanding of SDLC risks introduced by AI, including sensitive data exposure, prompt injection, insecure or improperly licensed generated code, and over-privileged agents, and mitigation through identity, policy, human oversight, and auditability.
• Demonstrated track record delivering platform capabilities that power consumer-facing software products, especially API- and event-driven systems.
• Deep experience adopting and operating within modern SDLC and engineering practices, including AI-enabled development, DevSecOps, CI/CD, GitOps, and platform-as-a-product.
• Thorough understanding of modern information security and data protection practices and their application across technology stacks in regulated environments.
• Collaborative, low-ego approach focused on business outcomes, with the ability to motivate and energize others and influence without authority.
• Exceptional communication skills and ability to navigate and influence at every organizational level, tailoring messages to different audiences.

Nice To Haves

• Experience in financial services or other regulated industries, including model risk management, responsible AI practices, emerging AI regulation, and their implications for architecture decisions.
• Experience measuring engineering productivity and the impact of AI adoption using frameworks such as DORA metrics, and leading change management to drive adoption at scale.
• Experience applying AI to modernize legacy platforms and codebases, such as mainframe or large monolithic applications.
• Hands-on experience with multiple model providers, agent frameworks, and major cloud providers’ AI services, including trade-offs in model selection, hosting, and cost.
• Undergraduate degree in Engineering, Computer Science, or another technical field.

Responsibilities

• Contribute platform thinking and subject matter expertise across platform domains, applying modern engineering and architectural patterns to systems such as APIs, services, events, data, UI, and supporting capabilities.
• Create and communicate best-practice target-state designs using cloud-native patterns, supported by artifacts such as business case and process context, context and sequence diagrams, and architecture decision records.
• Lead architecture and roadmap development for AI and agentic capabilities across the SDLC, including requirements and design assistance, AI-assisted coding, automated review and test generation, vulnerability and dependency remediation, documentation, and release and operational support.
• Define human-in-the-loop checkpoints and accountability for AI-generated changes.
• Define shared foundations for safe, scalable AI adoption, including governed model access and routing, agent orchestration and tool integration using standards such as MCP, retrieval over internal code and engineering knowledge, agent identity and least-privilege permissions, guardrails, audit trails, evaluation, observability, and AI cost management.
• Partner with Platform Engineering leaders to introduce, socialize, and champion modernization of front-end, middle-tier, and back-end technology stacks within an AI-first delivery model.
• Lead evaluations of new and existing vendors for alignment with Platform Engineering strategy, technology approach, and integration patterns.
• Define and drive adoption of integration patterns across internal systems, services, and capabilities so quality data, events, and services are available across channels.
• Partner with platform owners, product partners, and stakeholders to intake and evaluate platform capabilities and features, influencing design decisions before execution and delivery.
• Validate designs through hands-on proofs of concept and reference implementations, and contribute to architecture reviews and governance.
• Articulate the business value of the architectural roadmap, including fact-based future perspectives, options, and trade-offs aligned with business and engineering strategy.

What This Job Offers

• Job Type: Full-time
• Career Level: Principal
• Education Level: No Education Listed