Agentic AI Engineer - Vision AI

Responsibilities

• Design and implement Vision AI agents that combine perception models with reasoning and action
• Integrate LLMs and multimodal models with computer vision systems for enhanced decision-making
• Train and fine-tune deep learning models for object detection, tracking, and anomaly detection
• Optimize models for real-time inference on cloud and edge devices using quantization and compression
• Deploy Vision AI agents on edge devices, cameras, and cloud-native platforms
• Collaborate with Platform and AgentOps engineers to ensure scalability and observability
• Build evaluation pipelines to ensure safety, fairness, and real-world robustness

Requirements

• 2–5 years of experience in computer vision, ML engineering, or applied AI
• Proficiency in Python and deep learning frameworks such as PyTorch or TensorFlow
• Experience with object detection and recognition models like YOLO, Faster R-CNN, or SAM
• Knowledge of multimodal AI (combining vision and LLMs)
• Hands-on experience with cloud platforms (AWS, Azure, or GCP) and edge AI deployments
• Familiarity with inference optimization tools like ONNX, TensorRT, or OpenVINO

Preferred Qualifications

• Experience with emerging agentic AI frameworks such as LangGraph, CrewAI, or MCP
• Strong understanding of MLOps and CI/CD practices for AI systems

Benefits

• Continuous learning opportunities including certifications in Vision AI and MLOps
• Performance-based incentives and recognition for impactful solutions
• Comprehensive health insurance and wellness support
• Additional allowances for project-based roles and cab facilities for women employees

About the Company

XenonStack is a fast-growing Data and AI Foundry for Agentic Systems. We specialize in creating intelligent agents that combine reasoning, perception, and action to provide real-time business insights through platforms like Akira AI and XenonStack Vision AI.