Principal AI Engineer

Alkami is the digital sales and service platform provider for U.S. banks and credit unions. Our unified Platform integrates onboarding, digital banking, and data and marketing—each solution can stand alone, but together they deliver more—to help institutions onboard, engage, and grow relationships. As the future shifts toward Anticipatory Banking, we help data-informed bankers meet the moment with technology that drives action.Founded in 2009, we continue to be recognized for our intentional culture and tremendous growth (Best Place to Work in Fintech; Best & Brightest to Work For Nationally; and Comparably’s Best Company Culture, Best Career Growth, Best Engineering Team, and Best Places to Work in Dallas, among others). We’re building a culture where each Alkamist can perform to their highest potential, and we’re always on the lookout for the best and brightest minds. If you’re ready to experience the power of alchemy - transforming the ordinary into the extraordinary - come join one of the fastest growing SaaS companies in the U.S.As a remote-first company, most of our positions can be remote in the US, except for key roles, which will be indicated in the Job Title.Follow us on Glassdoor and LinkedIn!The Principal AI Engineer is a hands-on senior technical leader responsible for architecting and enabling AI augmented software engineering across the enterprise. This role drives the adoption of Generative AI, AI code assistants, and agentic workflows to transform the software development lifecycle (SDLC), accelerate engineering productivity, modernize legacy systems, and improve software quality. The individual will combine deep expertise in cloud-native architecture, distributed systems, and enterprise software development with advanced proficiency in AI-assisted engineering tools and agent frameworks. This role will design and implement AI-driven development platforms, agentic automation pipelines, and context-aware code generation capabilities that enable engineering teams to build and operate scalable, secure, and reliable software systems. As a Principal AI Engineer, this individual will influence enterprise architecture decisions, engineering productivity strategies, AI governance frameworks, and responsible AI adoption across the organization.Essential Duties & Responsibilities Lead & drive with hands-on coding experience, the enterprise adoption of AI-assisted development practices, integrating tools such as GitHub Copilot, Claude code, and other AI coding assistants into engineering workflows. Design and implement AI-augmented SDLC frameworks, enabling context-driven code generation, automated testing, and intelligent code review. Develop agentic automation systems to accelerate development tasks including bug fixing, code refactoring, documentation generation, and test automation. Build AI-enabled engineering platforms that integrate LLM capabilities directly into development environments and CI/CD pipelines. Design and implement agent-based engineering systems using frameworks such as n8n, OpenClaw, and other orchestration platforms. Develop multi-agent workflows for engineering automation including:Automated debugging,Intelligent test generation,Code remediation,Security vulnerability detection Implement architectures based on Agent frameworks, MCP (Model Context Protocol), and A2A (Agent-to Agent) communication protocols. Architect scalable, resilient cloud-native AI engineering platforms on modern cloud infrastructure. Drive enterprise architectural decisions related to AI-enabled development platforms, developer productivity systems, and AI engineering infrastructure. Implement Infrastructure-as-Code (IaC) practices and cloud automation frameworks. Design systems with strong focus on security, scalability, reliability, and cost optimization. Develop context-aware AI development systems that leverage codebases, documentation, architecture diagrams, and telemetry to improve code generation quality. Partner with platform engineering teams to integrate AI capabilities into CI/CD pipelines and DevOps platforms. Lead initiatives leveraging AI for large-scale legacy modernization, including automated code translation and refactoring. Design frameworks that use AI to migrate legacy systems to modern cloud-native architectures. Develop automation pipelines for codebase analysis, dependency mapping, and modernization strategies. Develop best practices for secure and ethical AI adoption within engineering workflows. Implement AI-driven telemetry, observability, and operational intelligence frameworks. Ensure AI-generated systems meet enterprise standards for security, reliability, and operational resilience. Provide technical mentorship and guidance to engineering teams adopting AI-augmented development practices. Lead architecture reviews and engineering strategy discussions related to AI-enabled software development. Influence engineering leadership on next-