Software Development Engineer I

About the role

Are you passionate about applying data science and artificial intelligence to solve some of the world’s biggest challenges? At Esri’s R&D Center in Sharjah, UAE, we are using cutting‑edge AI, deep learning and large language model techniques to revolutionize geospatial analysis and extract insight from satellite imagery. As a Software Development Engineer I you will create foundational and task‑specific models that empower GIS analysts and data scientists.

Key responsibilities

• Develop tools, APIs and pretrained models for deep‑learning and LLM workflows on imagery data.
• Build foundation models for computer vision, language, location and multimodal data.
• Create AI agents and assistants to automate various imagery tasks.
• Author and maintain sample applications showcasing AI/LLM capabilities across ArcGIS platforms.
• Conduct comparative studies of AI architectures to solve complex imaging problems.

Required profile

• At least 1 year of experience using Python for data science, deep learning and LLM projects.
• Self‑learner with strong knowledge of machine‑learning, deep‑learning and LLM concepts.
• Expertise in traditional and deep‑learning computer‑vision techniques (classification, detection, segmentation, GANs, super‑resolution, inpainting).
• Experience with transformer models applied to vision and natural‑language processing.
• Background in developing AI assistants or agents for specific tasks.
• Bachelor’s degree in computer science, engineering or a related field from a top‑tier institution.
• Valid work authorization for the United Arab Emirates.
• Preferred: experience applying deep learning to satellite or geospatial datasets and familiarity with the ArcGIS product suite.

Required skills

• Python programming.
• Deep‑learning frameworks (e.g., TensorFlow, PyTorch).
• Large language model development and fine‑tuning.
• Computer‑vision techniques such as image classification, object detection, segmentation, GANs.
• Transformer architectures for vision and NLP.
• Building and deploying AI assistants/agents.
• Multimodal foundation model construction and fine‑tuning.
• Experience with tools like LangGraph for multi‑agent orchestration.