Principal Software Engineer (Principal AI Engineer)

TL;DR

Principal Software Engineer (Principal AI Engineer): Design and implement production AI features across a fleet management portfolio, including scalable AI/ML models, AI-powered APIs/microservices, and LLM-powered capabilities with an accent on MLOps pipelines, responsible AI governance, and AI experimentation (A/B testing). Focus on establishing long-term AI strategy and best practices while mentoring engineers to ship reliable AI at production scale.

Location: Westlake, Texas

Company

hirify.global builds software solutions for fleet and transportation operations.

What you will do

• Design and implement production AI features for predictive maintenance, route optimization, driver behavior analysis, and fleet operations.
• Build scalable AI/ML models and services, including AI-powered APIs and microservices for web and mobile applications.
• Develop LLM-powered features (chatbots, natural language interfaces, document processing, automated insights) and reusable AI components/SDKs.
• Create AI experimentation frameworks and A/B testing infrastructure; modernize legacy systems with AI capabilities.
• Define AI strategy and roadmap, act as SME for AI adoption, and mentor engineers on AI/ML best practices and prompt engineering.
• Implement MLOps pipelines (training, deployment, monitoring, retraining) and responsible AI practices (bias detection, fairness, explainability, drift monitoring).

Requirements

• 10+ years of professional software engineering experience; 3+ years focused on AI/ML product development and delivery.
• 2+ years in a technical leadership position with a proven track record shipping AI-powered features to production at scale.
• Expert-level production experience with AI/ML applications, including supervised/unsupervised learning and deep learning frameworks (TensorFlow, PyTorch, JAX).
• Hands-on experience with LLMs/generative AI, prompt engineering, RAG, and fine-tuning.
• Strong MLOps and infrastructure experience: ML pipelines, model serving, monitoring/drift detection, and ML platforms (AWS SageMaker, Azure ML, Google Vertex AI, Databricks).
• Core backend and platform skills: Java (SpringBoot/SpringCloud), cloud (AWS/Azure/GCP), Docker and Kubernetes, plus vector databases for RAG (Pinecone/Weaviate/Chroma).

Nice to have

• PhD or Master’s degree in Computer Science, AI/ML, or related field.
• Experience with edge AI/IoT deployment, reinforcement learning, federated learning, and multimodal AI.
• Knowledge of AutoML/neural architecture search, graph neural networks, and geospatial AI/mapping technologies.
• Experience with telematics/ELD data analysis and transportation regulatory compliance (FMCSA, DOT).
• Background in conversational AI/chatbots and AI security/adversarial ML.

Culture & Benefits

• Hands-on role combining coding with technical leadership and mentoring.
• Emphasis on responsible AI standards, governance, and measurable production outcomes.
• Focus on AI innovation, experimentation, and continuous learning across engineering teams.
• Use of AI-assisted development tools to accelerate feature delivery.

Hiring process

• Interviews focused on AI/ML product delivery, production engineering, and technical leadership/mentoring experience.
• Discussion of AI strategy, MLOps, responsible AI practices, and architecture decisions for AI integration.