Lead AI Systems Engineer & Computer Vision

DataISource is hiring a lead engineer to design, build, and operate AI systems for its private AI platform. The role focuses on agent memory and knowledge graphs, production AI pipelines, and computer vision systems for industrial tracking, safety, and security.

Responsibilities:

• Help to build the knowledge graph and data pipelines behind our agentic AI, from processing through storage and lifecycle management
• Architect end-to-end AI pipelines for data ingestion, model training, deployment, and monitoring, built for reliability, performance, and security
• Develop, optimize, and deploy computer vision models for tracking, recording, correct sequential chain tracking, and safety and security use cases
• Run AI workloads in production, including private deployments where customer data stays under the customer’s control
• Diagnose and fix performance, reliability, and integration issues across models, services, and infrastructure
• Turn requirements from procurement and other industrial workflows into robust technical designs, working closely with product, data, and infrastructure teams
• Set our standards for documentation, testing, and CI/CD, mentor other engineers, and evaluate new technologies as the platform grows

Requirements:

• Experience leading the design and delivery of AI or computer vision systems in production, including mentoring other engineers
• Hands-on experience with computer vision frameworks such as PyTorch, TensorFlow, or OpenCV
• Experience deploying ML models at scale with tools like Docker, Kubernetes, and model-serving platforms
• Experience building agentic AI systems, including tool use and memory
• Data engineering experience across processing, storage, and lifecycle management
• Strong systems, infrastructure-as-code, AWS, and troubleshooting skills for AI workloads, from servers and cloud services to deployments and operational tooling
• Proficiency in Python and familiarity with distributed systems, APIs, and data pipelines
• Fluent professional English, written and spoken
• A degree in Computer Science, Mathematics, Physics, Electrical Engineering, or a related field, or equivalent practical experience
• Experience with knowledge graphs or graph databases
• C++ for performance-critical vision workloads
• Experience deploying AI in private or on-premise environments
• A background in industrial domains or enterprise software, especially procurement, manufacturing, or operations