Job Description
We are seeking a visionary Principal AI Architect to lead our engineering team in shaping the technology roadmap for 2026. In this pivotal role, you will design and implement scalable, next-generation Artificial Intelligence solutions that define the future of our industry.
As a key member of our leadership team, you will bridge the gap between theoretical research and production-grade engineering. You will be responsible for architecting our core LLM infrastructure and ensuring our systems are future-proofed for the rapid advancements expected in the coming years.
Why join us?
- Work on cutting-edge Generative AI and Large Language Model projects.
- Shape the technical direction for our 2026 and beyond initiatives.
- Competitive equity package and top-tier compensation.
- Flexible remote-first work environment.
Responsibilities
- Architecture & Design: Lead the end-to-end design of complex AI systems, focusing on scalability, security, and performance for the 2026 tech stack.
- Roadmap Planning: Define and drive the technical roadmap, identifying emerging technologies (e.g., Agentic AI, Edge AI) to maintain a competitive edge.
- Model Optimization: Oversee the optimization of inference pipelines and fine-tuning strategies for Large Language Models (LLMs).
- Talent Development: Mentor senior engineers and architects, fostering a culture of technical excellence and innovation.
- Stakeholder Collaboration: Translate complex technical concepts into clear strategies for product and executive leadership.
- Research & Implementation: Evaluate and integrate new research papers into production environments.
Qualifications
- Education: Master’s degree in Computer Science, Mathematics, or a related field (PhD preferred).
- Experience: 8+ years of experience in software engineering with at least 4 years specifically in AI/ML architecture.
- Technical Stack: Deep expertise in Python, PyTorch, TensorFlow, and Hugging Face.
- Cloud Mastery: Proven experience designing distributed systems on AWS, GCP, or Azure.
- System Design: Strong background in microservices, Kubernetes, and high-throughput data processing.
- Leadership: Demonstrated ability to lead high-performing engineering teams and drive technical decision-making.