AI Full-Stack Engineer

PFM is seeking an AI Full-Stack Engineer to design, develop, implement, and support enterprise AI solutions and modern business applications. The role combines full-stack engineering, artificial intelligence, data integration, cloud, DevOps, security, and governance responsibilities to deliver secure, scalable solutions that improve business operations and employee productivity.

Responsibilities:

• Design, develop, deploy, and maintain AI-powered applications, intelligent agents, and automation solutions
• Build AI workflows utilizing Large Language Models (LLMs), Retrieval Augmented Generation (RAG), prompt engineering, semantic search, and vector databases
• Develop reusable AI components, prompt libraries, templates, and services to accelerate future development
• Integrate AI capabilities into existing business applications and enterprise platforms
• Evaluate emerging AI technologies and recommend practical solutions that deliver measurable business value
• Monitor AI solution performance and continuously improve accuracy, reliability, cost efficiency, and user experience
• Design, develop, test, and maintain modern web applications using front-end and back-end technologies
• Build secure RESTful APIs, microservices, and system integrations
• Develop responsive user interfaces that provide intuitive access to AI-powered capabilities
• Create scalable application architectures that support enterprise growth and future enhancements
• Troubleshoot and resolve application issues while ensuring high availability and performance
• Develop integrations with enterprise applications, databases, document repositories, and cloud services
• Build data pipelines supporting AI applications and intelligent automation
• Design and maintain vector indexes and semantic search capabilities
• Ensure data quality, integrity, and security across all integrations
• Deploy and support applications across cloud and hybrid environments
• Develop and maintain CI/CD pipelines to automate application deployments
• Utilize containerization and orchestration technologies to improve scalability and reliability
• Monitor application health, logging, and operational performance
• Develop solutions that comply with enterprise security, privacy, and regulatory requirements
• Implement authentication, authorization, encryption, and secure coding practices
• Follow established AI governance standards, responsible AI principles, and data management policies
• Participate in architecture, security, and code reviews
• Partner with business leaders and subject matter experts to identify opportunities for AI-enabled process improvements
• Work closely with COO, Product Manager, Director of IT, and Software Developers throughout the solution lifecycle
• Prepare technical documentation, solution designs, and operational procedures
• Share knowledge and contribute to development standards and best practices