Job Description
We are at the precipice of a technological revolution, and Apex Future Systems is building the infrastructure for 2026 and beyond. We are seeking a visionary Lead AI Architect to define the architectural blueprint for our next-generation Artificial Intelligence ecosystem. In this pivotal role, you will bridge the gap between theoretical breakthroughs and scalable production systems, ensuring our AI solutions are robust, ethical, and ready to lead the market into the future.
As a key member of our CTO's office, you will drive the strategic direction of our AI initiatives, focusing on Generative AI, Autonomous Agents, and Quantum-Ready Neural Networks. If you thrive in ambiguity and want to shape the technology stack of tomorrow, this is your opportunity to make history.
Responsibilities
- Architectural Leadership: Design and implement high-scale AI/ML architectures that align with our 2026 strategic vision and long-term product goals.
- Model Engineering: Oversee the lifecycle of advanced models, including training, fine-tuning, and deployment of Large Language Models (LLMs) and multimodal systems.
- System Integration: Integrate AI capabilities into existing cloud infrastructure, ensuring seamless interoperability and high availability.
- MLOps & Scalability: Establish and optimize MLOps pipelines to accelerate model development cycles and ensure production-grade reliability.
- Team Mentorship: Lead a diverse team of data scientists and engineers, fostering a culture of innovation, technical excellence, and continuous learning.
- Future-Proofing: Research emerging technologies and frameworks to proactively adapt our architecture to the evolving landscape of 2026.
Qualifications
- Education: Bachelor’s or Master’s degree in Computer Science, Mathematics, or a related technical field; PhD preferred.
- Experience: 10+ years of software engineering experience, with 5+ years specifically in AI/ML architecture and leadership.
- Technical Stack: Deep expertise in Python, PyTorch, TensorFlow, and distributed systems.
- Cloud Mastery: Proven experience architecting solutions on AWS, GCP, or Azure with a focus on Kubernetes and serverless architectures.
- Generative AI: Strong understanding of transformer models, RAG (Retrieval-Augmented Generation), and prompt engineering techniques.
- Soft Skills: Exceptional communication skills with the ability to translate complex technical concepts for non-technical stakeholders.