Job Description
We are looking for a visionary Senior AI Architect to define the technological roadmap for 2026 and beyond. As we stand on the precipice of the next industrial revolution, you will be responsible for designing scalable, future-proof AI systems that integrate seamlessly with emerging enterprise infrastructures.
In this role, you won't just maintain legacy systems; you will architect the future of intelligence. You will lead a team of elite engineers in deploying next-generation Large Language Models (LLMs), agentic workflows, and neural processing units tailored for high-performance computing.
Why Join Us?
We offer a competitive compensation package, equity opportunities, and the chance to work on projects that define the trajectory of the tech industry for the decade ahead.
Responsibilities
- Architect Next-Gen AI Systems: Design and oversee the deployment of proprietary Machine Learning models and neural networks optimized for 2026 performance standards.
- Lead MLOps Transformation: Build robust, automated CI/CD pipelines for data science teams to ensure rapid iteration and model governance.
- Edge Computing Integration: Develop strategies for deploying complex AI models on edge devices, ensuring low-latency processing in real-time environments.
- Strategic Roadmapping: Collaborate with C-suite executives to translate business goals into technical AI roadmaps for the upcoming fiscal year.
- Ethical AI Governance: Establish frameworks to ensure AI transparency, fairness, and compliance with evolving global regulations.
- Team Leadership: Mentor junior engineers and data scientists, fostering a culture of innovation and continuous learning.
Qualifications
- Education: Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related technical field (PhD preferred).
- Experience: Minimum of 7 years of experience in software engineering with a focus on AI/ML architecture.
- Programming: Deep proficiency in Python, PyTorch, TensorFlow, or JAX.
- Cloud Expertise: Proven track record architecting solutions on AWS, GCP, or Azure.
- Vector Databases: Experience with Pinecone, Milvus, or Weaviate for RAG (Retrieval-Augmented Generation) implementations.
- Problem Solving: Demonstrated ability to solve complex, large-scale engineering problems in high-pressure environments.