Engineering Manager Computer Vision & AI (SiteGuard Squad Lead)📣 Job Ad

About WakeCap

WakeCap is a technology company that develops a connected-worker platform for large-scale construction and industrial sites. The platform integrates smart hardware, including helmets, anchors, and gateways, with a real-time SaaS solution to provide site teams with worker location tracking, safety compliance monitoring, automated mustering, and productivity analytics. WakeCap operates across major projects within the GCC region, including Al Khobar, Eastern Province, where this full-time role is based.

The Role: Engineering Manager, Computer Vision & AI (SiteGuard Squad Lead)

As the Engineering Manager, Computer Vision & AI (SiteGuard Squad Lead), you will lead the development of SiteGuard, WakeCap's computer vision safety product. SiteGuard utilizes site cameras to detect PPE non-compliance, hazards, and unsafe behavior in real time, operating both on edge devices and in the cloud to ensure consistent detection output. This role involves owning the entire technical stack, from detection models and camera agents to evaluation, MLOps pipelines, and the product surfaces that translate raw detections into actionable safety insights for HSE managers and site supervisors. You will lead a small, senior, and cross-disciplinary team, operating with significant autonomy and direct product impact.

Key Responsibilities

• Manage the full lifecycle of SiteGuard's detection capabilities, including PPE, hazards, and unsafe behavior, from problem framing and training to evaluation and production deployment.
• Define and implement model strategy across various detector types, including classical (YOLO family), transformer-based (RT-DETR, Co-DETR, GroundingDINO), zero/few-shot approaches (CLIP, DINOv2, SAM 2), and VLMs (Gemini Vision, GPT-4V, Qwen-VL) where they offer superior performance.
• Oversee the development of edge and cloud camera agents, focusing on optimized inference for constrained hardware (quantization, INT8/FP16, TensorRT, ONNX) and ensuring consistent output across deployment environments.
• Establish and maintain robust evaluation and MLOps practices, including a golden labeled dataset as the single source of truth, regression gates for quality assurance, experiment tracking, model registries, dataset versioning, and continuous monitoring of drift, cost, and accuracy.
• Lead the squad in hiring, performance management, fostering team culture, and ensuring successful delivery of product initiatives.

Required Qualifications and Experience

• A minimum of 10 years of experience in engineering, demonstrating progression from a senior Individual Contributor (IC) to a leadership role.
• At least 5 years of direct experience managing engineers, encompassing hiring, performance cycles, and addressing challenging conversations.
• Proven track record of deploying Computer Vision (CV) and Machine Learning (ML) systems into production, specifically involving high-throughput, asynchronous video and media processing.
• Strong proficiency in Python, with an emphasis on async-first development (asyncio, FastAPI or equivalent), and a focus on building reliability and observability into systems.
• Solid understanding of CV foundations, including classical and transformer-based detection and segmentation, video frame handling (OpenCV/FFmpeg), foundation models (CLIP, DINOv2, SAM 2), and VLMs for scene understanding.
• Experience with multimodal/VLM APIs (Gemini/Vertex, OpenAI, Anthropic), including prompt engineering, JSON-schema-constrained output, caching strategies, and per-model tuning.
• Expertise in edge inference optimization techniques (ONNX, TensorRT, quantization) and platforms such as Jetson, Hailo, or equivalent.
• Proficiency in MLOps practices, including experiment tracking, model registries, dataset versioning, and Continuous Integration (CI) for model evaluation.
• Daily hands-on experience with AI coding assistants like Claude Code and Codex, coupled with a grounded awareness of the current AI model landscape.

Compensation and Benefits

• Competitive salary, performance bonus, and equity package.
• Opportunity for a high-autonomy role focused on building a safety AI product from its foundational stages.
• Relocation support for candidates joining from outside the Kingdom of Saudi Arabia (KSA).
• Comprehensive health insurance, annual flights, and standard WakeCap employee benefits.

Work Type and Location

This is a full-time position based in Al Khobar, Eastern Province, Saudi Arabia.