Job Description
Architect the Future of Intelligence
We are FutureCore Technologies, a pioneer in next-generation infrastructure, seeking a visionary Next-Gen AI Architect to define our roadmap leading up to the year 2026.
In this role, you won't just maintain systems; you will engineer the very fabric of our future intelligence layer. You will bridge the gap between theoretical machine learning breakthroughs and scalable, production-grade infrastructure. If you are obsessed with the intersection of Generative AI, Quantum-ready architectures, and human-centric design, we want to meet you.
Why join us?
- Shape the technological trajectory for the next decade.
- Work with cutting-edge hardware and software stacks.
- Competitive compensation and equity packages.
Responsibilities
- Lead R&D for 2026 Roadmap: Design and prototype foundational models and infrastructure ready for the 2026 technological landscape.
- System Architecture: Design highly scalable, fault-tolerant systems that integrate deep learning models with cloud-native architectures.
- Optimization & Performance: Implement advanced optimization techniques to reduce latency and increase throughput for real-time AI inference.
- Strategic Collaboration: Partner with product managers and engineering leads to translate business goals into technical roadmaps.
- Team Mentorship: Foster a culture of innovation by mentoring junior engineers and conducting technical workshops on AI/ML best practices.
- Data Strategy: Define data pipelines and governance protocols to ensure high-quality training data for our models.
Qualifications
- Experience: 7+ years of experience in software engineering, with at least 3 years specifically in AI/ML infrastructure or large-scale system architecture.
- Programming Mastery: Deep expertise in Python, C++, or Rust, with a strong understanding of distributed systems.
- Machine Learning: Hands-on experience with training, fine-tuning, and deploying large language models (LLMs) and neural networks.
- Cloud Proficiency: Proven track record with AWS, GCP, or Azure, specifically utilizing containerization (Docker/Kubernetes) and serverless technologies.
- Education: Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, or a related technical field.
- Problem Solving: Ability to tackle complex, unstructured problems with creative engineering solutions.