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 (AWS, Azure, or GCP)

Proficiency with containerization (Docker) and orchestration (Kubernetes)

Experience with vector databases (Pinecone, Weaviate, Chroma) for RAG applications

Strong background in both relational and NoSQL databases

Knowledge of data engineering and ETL pipelines

Responsible AI & Governance

Understanding of AI ethics, bias detection, and fairness

Experience with model explainability techniques (SHAP, LIME)

Knowledge of AI compliance and regulatory requirements

Privacy-preserving ML techniques

Model monitoring for drift, degradation, and anomalies

AI Strategy & Leadership

Identifying high-ROI AI opportunities aligned with business goals

Building business cases for AI investments

Evaluating build vs. buy vs. partner decisions for AI capabilities

Understanding AI cost optimization and resource management

Experience with AI product lifecycle from concept to production

Leadership & Communication

Exceptional communication skills with ability to influence engineering and product leadership

Strong mentorship mindset with proven impact on elevating teams

Ability to translate complex AI concepts for non-technical stakeholders

Track record of making architectural decisions and defending technical choices

Collaborative mindset focused on enabling AI adoption across teams

Experience creating training programs and educational content

Soft Skills

Bias toward action and shipping working AI solutions

Passion for AI innovation balanced with pragmatic delivery

Strong problem-solving and debugging skills for complex AI systems

Ability to manage multiple AI initiatives simultaneously

Comfortable challenging the status quo constructively

Customer-centric mindset when designing AI features

NICE TO HAVE

PhD or Master's degree in Computer Science, AI/ML, or related field

Experience with edge AI and model deployment on IoT devices

Knowledge of reinforcement learning for optimization problems

Familiarity with federated learning for distributed data

Experience with AI-powered analytics and business intelligence

Background in conversational AI and chatbot development

Understanding of multimodal AI (vision + language)

Experience with AutoML and neural architecture search

Knowledge of graph neural networks for route optimization

Familiarity with geospatial AI and mapping technologies

Experience with Electronic Logging Device (ELD) data analysis

Background in telematics and sensor data processing

Understanding of regulatory compliance in transportation (FMCSA, DOT)

Experience with AI security and adversarial ML

EDUCATION

Bachelor's degree in Computer Science, AI/ML, Data Science, or equivalent practical experience (Master's or PhD preferred)

WHAT SUCCESS LOOKS LIKE

You're consistently shipping AI-powered features that deliver measurable business value

Multiple teams across the organization are successfully leveraging AI capabilities

Engineering productivity has improved through widespread adoption of AI development tools

The organization has clear AI strategy, standards, and best practices

AI model performance and reliability meet or exceed production SLAs

Engineers you mentor are effectively using AI tools and building AI features

Legacy systems are being enhanced with modern AI capabilities

AI experimentation velocity has increased with proper governance

You've established the organization as a leader in AI-powered fleet management

Teams are making informed build/buy/partner decisions on AI capabilities

You're known as the person who makes AI practical, accessible, and impactful

EQUAL OPPORTUNITY EMPLOYER SOLERA HOLDINGS, INC., AND ITS US SUBSIDIARIES (TOGETHER, SOLERA) IS AN EQUAL EMPLOYMENT OPPORTUNITY EMPLOYER. THE FIRM'S POLICY IS NOT TO DISCRIMINATE AGAINST ANY APPLICANT OR EMPLOYEE BASED ON RACE, COLOR, RELIGION, NATIONAL ORIGIN, GENDER, AGE, SEXUAL ORIENTATION, GENDER IDENTITY OR EXPRESSION, MARITAL STATUS, MENTAL OR PHYSICAL DISABILITY, AND GENETIC INFORMATION, OR ANY OTHER BASIS PROTECTED BY APPLICABLE LAW. THE FIRM ALSO PROHIBITS HARASSMENT OF APPLICANTS OR EMPLOYEES BASED ON ANY OF THESE PROTECTED CATEGORIES.