Principal, AI Engineer

Volante Technologies is the leading global provider of low-code cloud Payments as a Service solution for financial businesses. We are disruptors and innovators and we are growing fast. For the last three years, we have been the #1 seller of wholesale payment systems worldwide. At Volante, we are all about revolutionizing the world of Payments. Role Summary We are seeking a Principal AI Engineer to provide technical leadership for the enterprise AI platform and AI-powered products. This individual will define architecture, establish engineering standards, drive AI innovation, and mentor engineering teams. What You’ll Do (Key Responsibilities) Technical Leadership Define enterprise AI architecture and technology roadmap. Lead design and implementation of AI platforms, AI agents, and AI-powered products. Drive adoption of GenAI across software engineering, operations, and customer-facing products. Establish standards for model selection, evaluation, governance, security, and observability. Review architecture and provide technical direction for critical initiatives. Platform Engineering Build scalable AI platforms supporting RAG, Agentic Workflows, MCP Integrations, Multi-model Orchestration, Model Evaluation Frameworks, Prompt Management, and AI Observability. Design AI infrastructure leveraging cloud-native technologies. Engineering Excellence Define coding standards and AI engineering best practices. Establish AI SDLC processes. Drive CI/CD and MLOps adoption. Lead performance optimization and cost governance initiatives. Innovation Evaluate emerging AI technologies and foundation models. Define build-vs-buy strategies. Drive POCs and incubate new AI capabilities. Collaborate with customers and business stakeholders to identify AI opportunities. People Leadership Mentor junior and senior AI engineers. Conduct technical interviews and talent assessments. Develop AI competency frameworks. Act as a technical advisor to engineering leadership. What You Bring (Skills & Qualifications) Required Skills: LLMs, Foundation Models, Agentic AI, RAG, Fine-tuning, Prompt Engineering AI Governance and Responsible AI Python, Java, Distributed Systems, Event-Driven Architecture, Microservices LangChain, LlamaIndex, AutoGen, CrewAI, Semantic Kernel MLFlow, Azure ML, SageMaker, Model Lifecycle Management Vector Databases, Data Pipelines, Knowledge Graphs Azure, AWS, Kubernetes, Terraform, CI/CD Platforms Preferred Qualifications: 10–15+ years in software engineering. 5+ years in AI/ML or Data Engineering. 2+ years in Generative AI solutions.