Job Description
We are seeking a visionary Future Tech Lead to architect the AI infrastructure that will define the landscape of 2026 and beyond. At Nexus Core Systems, we are not just predicting the future; we are engineering it. You will be at the forefront of the next industrial revolution, leading the development of autonomous systems and generative intelligence platforms.
In this high-impact role, you will bridge the gap between cutting-edge AI research and scalable production engineering. You will lead a team of elite engineers tasked with solving complex, multi-modal problems that push the boundaries of current technology. If you are passionate about building the systems that will power the world of tomorrow, this is your opportunity.
Why join us?
• Competitive compensation package.
• Equity stake in a rapidly growing enterprise.
• Work on projects that define the industry standard for 2026.
Responsibilities
- Define the long-term architectural roadmap for AI systems, ensuring readiness for 2026 and beyond.
- Lead the design, training, and deployment of large-scale machine learning models and neural networks.
- Collaborate with product leaders to translate futuristic concepts into feasible, high-quality engineering solutions.
- Mentor senior engineers and foster a culture of innovation, technical excellence, and ethical AI practices.
- Optimize existing systems for efficiency, scalability, and performance in real-world environments.
- Stay ahead of industry trends in AI, Quantum Computing, and Edge Intelligence.
Qualifications
- 10+ years of experience in software engineering, with at least 5 years specifically in AI/ML architecture and leadership.
- Deep proficiency in Python, TensorFlow, PyTorch, or JAX, with experience in distributed computing frameworks.
- Proven track record of leading cross-functional teams in a high-growth, fast-paced environment.
- Strong understanding of cloud architecture (AWS, GCP, or Azure) and containerization (Docker, Kubernetes).
- Excellent communication skills, capable of explaining complex technical strategies to non-technical stakeholders.
- Experience with ethical AI frameworks and bias mitigation in large datasets.