About the Company

Join our team with our newly added Senior AI Engineer role! We are seeking a talented and experienced senior level engineer with a background in generative AI and machine learning to join our innovative engineering team. In this role, you will contribute to the design, development, and maintenance of full-stack software solutions, with a focus on integrating AI/ML technologies to enhance our products and services.

Over $20 trillion of freight moves through the U.S. economy every year, and most of it is still managed through fragmented data, manual processes, and knowledge that lives in people’s heads. We’re changing that. We're building agentic AI that can reason through complex, customer-specific freight scenarios and operate reliably in workflows where the stakes are measured in real dollars. Agentic capability is becoming the foundation of how every product in our portfolio works. This is not a side project. You’ll join a team of engineers, product managers, and domain experts building production agentic systems from the ground up.

Freight is a deceptively complex domain: fragmented data sources, constantly shifting constraints, and an ecosystem of carriers, shippers, and intermediaries that doesn’t sit still. The problems you’ll work on include:

Designing agent reasoning that navigates complex, customer-specific freight scenarios
Solving entity resolution and data integration across diverse data sources
Building evaluation and reliability frameworks that prove agent decisions are sound before they touch customer workflows
Defining orchestration patterns that scale from a single product to platform-wide agentic capability

You’ll work with years of real, proprietary freight data. You’ll influence how these agents interact with users, working alongside product, design, and domain experts. This is not a research role. We ship. But the people who thrive here think deeply about how agents should work, not just how to make them work right now. If you’ve been building agentic systems and want to see what happens when they meet a hard, real-world domain with real data and real consequences, this is where that work happens.

About the Role

Generative AI and Machine Learning Development: Implement and integrate generative AI models and machine learning algorithms into existing and new software solutions. Fine-tune and optimize pre-trained AI/ML models for specific use cases. Collaborate with engineers and data scientists to build and deploy scalable AI-driven features.

Responsibilities

Full Stack Development: Write clean, efficient, and maintainable code for AI-powered software applications. Contribute to both frontend and backend development tasks as part of a cross-functional team, ensuring seamless integration of AI components.
Architectural Design: Work closely with team members and product leads to understand requirements, design AI/ML-enabled features, and contribute to product success. Participate in architectural discussions to determine the best ways to incorporate AI technologies into existing systems.
Technical Excellence: Actively seek opportunities to learn about emerging AI/ML techniques, tools, and platforms. Optimize and refactor code to address performance bottlenecks in AI/ML pipelines. Write and execute robust unit and integration tests for AI/ML models and other software components. Troubleshoot and resolve issues related to AI/ML model performance and system integration.
Innovation: Stay updated on cutting-edge advancements in AI/ML, particularly in generative AI models. Propose and implement creative solutions using AI to solve business problems and enhance user experiences.
Collaboration: Partner with senior, staff, and principal engineers to refine development processes for AI/ML integration. Share knowledge about AI/ML best practices with teammates and mentor junior engineers interested in the field.

Qualifications

Bachelor’s degree in Computer Science or related technical field involving coding (e.g., physics or mathematics), or equivalent technical experience
7+ years as a software or data engineer
2+ years experience in AI/ML engineering
Experience using AI/ML libraries and frameworks (e.g., Google ADK, LangChain/Graph, Anthropic, GPT, Gemini, Llama, Vertex, TensorFlow, Scikit-learn) training and fine-tuning machine learning models, including supervised, unsupervised, and reinforcement learning approaches.
Proficiency in multiple programming languages, frameworks, and technologies such as Python, SQL, ReactJS, Node.js, JavaScript, TypeScript, Apache Beam, dbt, and BigQuery.
Knowledge of application architectures, security best practices, and data integration concepts.
Exposure to modern infrastructure such as code technologies like Docker, Kubernetes, Terraform, and Airflow.
Understanding of database concepts, data modeling, and data warehousing principles.
Understanding of distributed data management systems and related applications.
Familiarity with public cloud infrastructure design, tools, and strategies.
Knowledge of software development methodologies including Agile, Kanban, and Scrum.
Effective communication skills, with the ability to articulate technical concepts to both technical and non-technical stakeholders.

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