Agentic AI/ Edge Computing SW Engineer

Design, develop, and test a variety of AI-driven software assignments as part of a larger project. Contribute to the implementation of production-grade AI agent systems, from single-purpose agents to more complex frameworks. Develop and maintain AI-powered applications on Android platforms, including creating data pipelines to on-premises servers for AI processing. Implement and maintain data pipelines between mobile devices and AI servers, leveraging knowledge of networking technologies. Collaborate with senior engineers to develop and integrate AI agents into our New Product Development playbooks. Participate in project code reviews and provide input on software design. Implement AI model pipelines, including data preprocessing and inference, into software systems. Conduct rigorous testing of AI models and software to ensure reliability, accuracy, and compliance with requirements; review test results and perform root cause analysis to identify problems. Make changes or upgrades to existing software, enhancing and improving existing technologies to apply to new solutions. Create and maintain technical documentation for software, APIs, and system components. Stay up to date with the latest AI and software development tools, frameworks, and technologies to drive innovation. Bachelor's degree in Computer Science, Engineering, or a related discipline. 2+ years of professional software development experience, or a Master's degree with relevant project/internship experience. At least 1 year of practical exposure to AI/ML systems, frameworks, or AI-enabled applications (can be through projects, internships, or professional work). Proficiency in Python and experience with modern AI frameworks and libraries (e.g., LlamaIndex, LangChain, OpenAI APIs, TensorFlow/PyTorch, Hugging Face). Experience with Docker Containers and Kubernetes Understanding of networking concepts and data transfer protocols (e.g., REST APIs). Familiarity with AI agent concepts such as planning, tool use, and reasoning. Solid software engineering fundamentals, including data structures, algorithms, and version control (Git). Master's degree in a relevant field. Experience with or knowledge of Android application development. Knowledge or previous projects in training and fine tuning AI models is highly desired. Knowledge of Retrieval-Augmented Generation (RAG) and its integration with vector databases. Experience with MLOps and deploying AI/ML models in a cloud environment (e.g., AWS, GCP, Azure). Exposure to Nvidia CUDA toolkit. Familiarity with Agent Development Kits (ADK). Experience building or contributing to multi-agent systems. Experience integrating AI solutions with enterprise tools and APIs. A pragmatic, "builder" mindset with a passion for prototyping and iterative development. Excellent problem-solving skills and an eagerness to tackle complex challenges. Good understanding of software engineering principles (e.g., system design, CI/CD). Strong collaboration and communication skills. Curiosity and a drive to learn new technologies.