Principal Software Engineer

JOB SUMMARY We're looking for a pragmatic, hands-on Principal AI Engineer who gets things done. You'll spend significant time writing code while helping elevate the technical skills of the broader organization. This role is ideal for someone who thrives on building and delivering AI-powered products and features, has extensive experience leveraging AI development tools to accelerate delivery, and excels at establishing AI strategy and best practices across an entire fleet management portfolio. You'll balance individual contribution with strategic technical leadership, serving as the subject matter expert (SME) for AI technology adoption, helping teams integrate AI capabilities into applications, and mentoring engineers on how to develop effectively with AI-assisted tools. WHAT YOU'LL DO Build and Ship Design and implement production AI features and capabilities across the fleet management portfolio Build scalable AI/ML models and services for predictive maintenance, route optimization, driver behavior analysis, and fleet operations Develop AI-powered APIs and microservices that serve multiple web and mobile applications Leverage and evangelize AI-powered development tools (GitHub Copilot, Cursor, ChatGPT, Claude, etc.) to accelerate feature development Create reusable AI components, SDKs, and libraries that reduce duplication across teams Modernize legacy systems by integrating modern AI capabilities Implement LLM-powered features (chatbots, natural language interfaces, document processing, automated insights) Build AI experimentation frameworks and A/B testing infrastructure Lead Through Example Define the long-term AI strategy and roadmap for the fleet management platform Serve as the organizational SME for AI technology adoption and implementation Champion and integrate emerging AI technologies that solve real business problems Mentor engineers on AI/ML best practices, prompt engineering, and AI-assisted development Establish standards for responsible AI development, model governance, and ethical AI use Share best practices for using AI development tools to maximize productivity Guide architectural decisions for AI feature integration across the platform Foster a culture of AI innovation, experimentation, and continuous learning Technical Execution & Strategy Partner with product, engineering, and business teams to identify high-impact AI opportunities Evaluate and select appropriate AI/ML frameworks, models, and platforms for different use cases Design MLOps pipelines for model training, deployment, monitoring, and retraining Implement responsible AI practices including bias detection, fairness, and explainability Create comprehensive documentation, playbooks, and training materials for AI adoption Build monitoring and observability for AI model performance and drift detection Collaborate with data teams on feature engineering, data pipelines, and model training infrastructure Drive proof-of-concepts and experiments to validate AI opportunities REQUIRED QUALIFICATIONS Experience 10+ years of professional software engineering experience 3+ years focused on AI/ML product development and delivery 2+ years in a technical leadership position Proven track record of shipping AI-powered features to production at scale Extensive experience using AI-assisted development tools in daily workflows History of establishing AI practices and strategies across engineering organizations Experience in fleet management, transportation, logistics, or IoT domains preferred Track record of mentoring and growing technical talent Willingness to maintain hands-on technical involvement AI/ML Product Development Expert-level experience building production AI/ML applications Strong background in supervised and unsupervised learning algorithms Hands-on experience with deep learning frameworks (TensorFlow, PyTorch, JAX) Production experience with Large Language Models (LLMs) and generative AI Knowledge of prompt engineering, RAG (Retrieval Augmented Generation), and fine-tuning Experience with computer vision for applications like driver monitoring or vehicle inspection Understanding of time-series analysis and forecasting for fleet operations Experience with recommender systems and optimization algorithms AI-Assisted Development Expertise Deep expertise using AI coding assistants (GitHub Copilot, Cursor, Cody, etc.) in production Proven ability to train teams on effective AI-assisted development practices Understanding of prompt engineering for code generation and debugging Knowledge of when and how to leverage AI tools for maximum productivity Experience establishing organizational standards for AI tool usage Fleet & Transportation AI Use Cases Predictive maintenance and failure prediction models Route optimization and dynamic routing algorithms Driver behavior analysis and safety scoring Fuel efficiency optimization and cost reduction Demand forecasting and capacity planning Natural language processing for logs, reports, and documentation Anomaly detection for vehicle health and operations Computer vision for safety, compliance, and inspections MLOps & Infrastructure Designing and implementing ML pipelines and model serving infrastructure Experience with ML platforms (AWS SageMaker, Azure ML, Google Vertex AI, Databricks) Knowledge of model versioning, experiment tracking (MLflow, Weights & Biases) Building automated retraining and monitoring pipelines Understanding of model deployment patterns (batch, real-time, edge) Experience with model compression and optimization for production Feature stores and data versioning tools Core Technical Skills Expert-level proficiency in Java and ML/AI libraries (SpringAI, LangChain4J) Strong experience with modern backend development (SpringBoot, SpringCloud, Java21+alk, or similar) Hands-on experience with cloud platforms (AW