Principal AI Platform Engineer

This is a fully remote position, open to applicants in Alabama.

📋 Description

• Design, develop, and maintain enterprise-level GenAI solutions, which encompass AI-assisted development, documentation, testing, analytics, and workflow automation.

• Lead the architecture, implementation, and optimization of Retrieval-Augmented Generation (RAG) solutions, focusing on ingestion pipelines, embeddings, vector stores, retrieval frameworks, and search functionalities.

• Create, review, and approve architectures for agent-based and tool-integrated AI systems, including multi-step LLM workflows.

• Develop and manage APIs, shared services, and reusable frameworks that connect AI models with internal systems, platforms, and authorized third-party tools.

• Set standards for prompt engineering, create evaluation methodologies, and establish testing frameworks.

• Oversee model testing, benchmarking, evaluation, and performance analysis, adhering to approved frameworks and governance standards.

• Write secure, scalable, and maintainable code in Java, Python, and C#, while advocating for engineering excellence.

• Facilitate technical discussions with Product Managers, Architects, Engineers, and senior stakeholders to translate business objectives into enterprise-level AI solutions.

• Act as a subject matter expert in Generative AI, AI platform engineering, and responsible AI practices.

• Coach and mentor engineers on software engineering, AI architecture patterns, algorithms, data structures, and enterprise platform design.

• Contribute to technical roadmaps that balance strategic AI initiatives, platform modernization, innovation, operational excellence, and reduction of technical debt.

• Define and promote architecture standards, design patterns, and implementation guidelines for AI-enabled solutions.

• Utilize engineering, operational, and AI performance metrics to identify opportunities for process improvements and platform optimization.

• Lead best practices related to resiliency, performance, observability, and security within AI platforms and services.

• Advocate for responsible AI, model governance, security, compliance, privacy, and risk management throughout the AI development lifecycle.

• Engage in and present at enterprise architecture forums, engineering councils, and leadership committees.

• Comply with company risk and regulatory standards, policies, controls, and Risk Appetite; escalate any risk-related concerns.

• Maintain internal control standards and implement internal/external audit and regulatory findings as necessary.

• Perform other related duties as assigned.

⛳️ Requirements

• Associate’s degree with at least 9 years of systems analysis and/or application development work experience, or a Bachelor's degree with a minimum of 7 years of such experience.

• Alternatively, a combined minimum of 11 years of education and/or relevant work experience, including at least 7 years in systems analysis and/or application development.

• Expertise in at least 1 relevant programming language and advanced proficiency in at least 1 additional relevant programming language.

• Strong understanding of software engineering principles, data structures, algorithms, and distributed system design.

• Practical experience in developing production applications using Java, Python, C#, or other modern enterprise programming languages.

• Experience in designing and integrating RESTful APIs, microservices, and API-driven architectures.

• Advanced knowledge of Generative AI, Large Language Models (LLMs), prompt engineering, and AI application development.

• Experience in building and supporting AI-enabled applications within enterprise SDLC, security, compliance, and governance frameworks.

• Proven capability to influence technical direction, engineering standards, and architectural decisions across various teams.

• Preferred: experience implementing enterprise Generative AI solutions in financial services or other highly regulated industries.

• Preferred: expertise in Retrieval-Augmented Generation (RAG), embeddings, vector databases, retrieval frameworks, and semantic search technologies.

• Preferred: understanding of Transformer architectures, attention mechanisms, tokenization strategies, and model evaluation techniques.

• Preferred: experience in designing AI agents, tool-integrated workflows, and advanced LLM orchestration frameworks.

• Preferred: expertise in Microsoft Azure, Azure AI Services, OpenAI technologies, and cloud-native AI platforms.

• Preferred: experience in establishing enterprise AI governance, responsible AI practices, and model risk management controls.

• Preferred: experience leading large-scale technical initiatives, platform modernization efforts, or enterprise capability rollouts.

• Preferred: experience influencing senior technology and business stakeholders and driving the enterprise-wide adoption of new technologies.

• Preferred: ability to work independently while managing complex technical initiatives across multiple teams.

• Preferred: advanced verbal and written communication skills, capable of presenting complex technical concepts to executive audiences.

• Preferred: subject matter expertise in AI platform engineering, software architecture, and enterprise application development.

• Preferred: experience with CI/CD pipelines, DevOps tooling, automated testing, observability, and platform reliability engineering practices.

🏝️ Benefits

• Comprehensive health insurance plans.

• Competitive salary and performance-based bonuses.

• Opportunities for professional development and continuous learning.

• Flexible work hours and remote work options.

• Generous paid time off and holiday leave policies.