Principal Software Engineer

Insight Global is looking for a machine‑learning‑first Principal Engineer who can architect and lead AI systems for operational decision‑making, explain technical tradeoffs clearly, prototype solutions hands‑on, and guide other engineers. This person we hire will lead the design and application of AI‑driven decision systems for warehouse operations. This role is focused on using machine learning, computer vision, and LLMs to improve operational outcomes—such as picking, carton flow, and goods‑to‑person workflows—beyond what traditional rules‑based or algorithmic systems can achieve. This is not a developer‑productivity or “AI to write code faster” role. The emphasis is on AI for operational decision‑making in real‑world environments. The ideal candidate is a machine‑learning‑first engineer who can architect systems, lead technical direction, and prototype solutions, while guiding other engineers through clear design patterns and interfaces.

AI & Machine Learning Leadership

• Serve as the technical lead for AI initiatives within warehouse and fulfillment operations.
• Design and implement machine learning–driven decision systems that outperform rule‑based approaches.
• Select and justify appropriate ML techniques (e.g., supervised/unsupervised learning, optimization, genetic algorithms, neural networks) based on problem constraints and tradeoffs.
• Compare and evaluate AI‑based approaches against existing algorithmic or rules‑based systems.

System Architecture & Technical Direction

• Architect end‑to‑end AI systems, including:
• Model pipelines
• Interfaces between services
• Orchestration of AI agents and sub‑agents
• Cloud deployment patterns
• Clearly communicate architectural designs to Java and Python developers, even if not coding every component personally.
• Define design patterns, interfaces, and system boundaries for scalable, maintainable solutions.

Hands‑On Prototyping

• Build prototypes and proofs of concept, especially in early‑stage or small‑team environments.
• Work closely with a small AI team (initially partnering with a senior engineer) and help shape the future structure of the function.

Collaboration & Operational Understanding

• Partner with operations, engineering, and robotics teams to translate real‑world warehouse workflows into AI‑driven solutions.
• Spend time onsite in warehouses to understand operational realities (travel required).
• Support go‑lives and iteration cycles for deployed AI systems.

Requirements:

• Deep expertise in Machine Learning
• Strong understanding of ML algorithms, model selection, tradeoffs, and limitations
• Ability to clearly explain why one approach is chosen over another
• Strong Python proficiency for ML development
• Experience with frameworks such as PyTorch, scikit‑learn, or similar
• Principal‑level engineering capability
• Proven experience designing and architecting complex systems
• Ability to lead and guide other engineers technically
• Strong software architecture fundamentals
• Solid grasp of object‑oriented programming concepts and design patterns
• Ability to communicate designs effectively to Java developers
• Experience with Computer Vision
• Object detection, image/video processing, or vision‑based ML systems
• Working knowledge of LLMs
• Understanding of how LLMs can be applied, integrated, and orchestrated
• Does not need to be an LLM specialist
• Cloud experience
• GCP experience is preferred, but AWS/Azure backgrounds are acceptable

Plusses:

• Prior experience in warehouse, fulfillment, or distribution environments
• Familiarity with robotics, automation, or AI‑driven operational systems
• Exposure to IoT concepts (protocols are not required)
• Experience transitioning from rule‑based systems to ML‑driven solutions