3+ years experience (5+ preferred) building and shipping production AI systems, ideally agentic products
Experience as an early engineer at a VC-backed startup, taking systems from 0 to 1
Comfortable working autonomously in a fast-paced, high-intensity environment with high ownership
Track record building enterprise AI platforms that handle complex, physical-world data (video, IoT, sensor streams)
Bonus: experience in robotics, autonomous systems or industrial computer vision
What you have done
Built and shipped agent systems in production with orchestration, tool use, state management and human-in-the-loop workflows
Worked with physical-world data at scale (RTSP video, time-series telemetry, vibration, thermal, PLC / OPC-UA) under real constraints (noise, drift, latency, alignment)
Built multimodal AI pipelines combining vision (detection, segmentation, action recognition) with structured operational data
Designed or contributed to ontology, knowledge graph or structured context systems grounded in real asset hierarchies and processes
Integrated AI systems with ERP, CMMS, WMS, historians or PLC layers and handled normalization and schema mapping
Shipped end-to-end systems from ingestion and model serving through backend services (Python, TypeScript) to frontend interfaces
What you will build
Agent runtime and orchestration across Vision Quality, Predictive Maintenance and Operations Planning agents
Context assembly from ontology and memory, tool dispatch, approval gates, tracing and cost controls
Multimodal sensor pipelines: video processing, YOLO / segmentation, FFT feature extraction and cross-sensor correlation
Industrial ontology / knowledge graph mapping plants, assets, sensors, work orders, materials and maintenance history
Memory layer including trace storage, playbooks, asset templates and transferable failure pattern libraries
Operational decision surfaces: dashboards, alerting workflows with evidence, replanning tools and audit trails
Integration connectors across ERP, CMMS, WMS and PLC systems into a unified schema
Who you are
Have built AI systems from 0 to production in real environments
Strong background in AI/ML applied to physical-world systems
Understand that the hardest problems are in data ingestion, normalization, temporal alignment and ground truth
Think in terms of production systems: reliability, failure modes, cost and human interaction
Comfortable operating in a high-intensity, fast-moving environment with significant ownership
Motivated to work on real-world industrial problems that require both depth and execution
About Serious AI
Serious AI is an AI and automation company focused on solving complex problems in heavy industries such as utilities, oil & gas, logistics, and manufacturing. The company builds end-to-end AI platforms, custom models, and enterprise AI strategies that help organizations optimize operations, reduce downtime, and improve efficiency. Its solutions include predictive maintenance, supply chain optimization, fleet management, and outage response systems powered by advanced data and machine learning. Serious AI aims to “rebuild the industrial base” by combining deep industry expertise with cutting-edge AI engineering to deliver measurable operational outcomes for large enterprises.
