Job Description
Are you ready to define the technological landscape of 2026 and beyond? Aethelgard Technologies is at the forefront of the AI revolution, building the next generation of intelligent systems that will reshape industries. We are seeking a visionary Senior AI Architect to lead our strategic roadmap and engineering efforts.
In this pivotal role, you won't just be maintaining systems; you will architect the future. You will be responsible for designing scalable, high-performance AI infrastructure that integrates seamlessly with emerging technologies like quantum computing and edge AI. Join us in creating the solutions that will power the decade ahead.
Why Join Us?
- Work on cutting-edge projects with a team of world-class engineers.
- Competitive compensation and equity package.
- Flexible remote and hybrid work options.
- Professional development opportunities and leadership training.
Responsibilities
- Lead the architectural design and implementation of AI models and infrastructure for the 2026 product roadmap.
- Oversee the full machine learning lifecycle, from data ingestion and feature engineering to model training and deployment.
- Collaborate with cross-functional teams (Product, Data Science, Engineering) to define technical requirements and deliver high-quality solutions.
- Optimize existing algorithms for performance, scalability, and cost-efficiency on cloud-native platforms.
- Establish best practices for code quality, testing, and CI/CD pipelines within the AI engineering team.
- Stay abreast of the latest advancements in AI, NLP, and computer vision to drive innovation within the organization.
- Mentor junior engineers and architects, fostering a culture of continuous learning and technical excellence.
Qualifications
- Ph.D. or Master’s degree in Computer Science, Mathematics, or a related field.
- Minimum of 8 years of experience in software engineering, with at least 5 years specializing in Artificial Intelligence and Machine Learning.
- Strong proficiency in Python, TensorFlow, PyTorch, or similar deep learning frameworks.
- Proven experience designing distributed systems and scalable microservices architectures.
- Deep understanding of statistical modeling, neural networks, and large language models (LLMs).
- Experience with cloud platforms (AWS, GCP, or Azure) and containerization tools (Docker, Kubernetes).
- Excellent problem-solving skills and the ability to communicate complex technical concepts to non-technical stakeholders.