Job Description
We are at the precipice of a technological renaissance. Nexus Future Labs is looking for a visionary Lead AI Strategist to spearhead our 2026 Initiative. In this pivotal role, you won't just be building models; you will be architecting the cognitive infrastructure of tomorrow. You will work directly with our C-suite to define the roadmap for next-generation artificial intelligence, ensuring our solutions are not only scalable and robust but also ethically sound and transformative.
Join a team of world-class engineers, ethicists, and futurists dedicated to pushing the boundaries of what is possible. If you are driven by the challenge of solving complex problems and have a passion for shaping the future of humanity through technology, we want to hear from you.
Responsibilities
- Define and execute the technical roadmap for the 2026 AI product suite, focusing on generative AI and predictive analytics.
- Lead a high-performance cross-functional team of data scientists, engineers, and product managers.
- Conduct high-level research to identify emerging trends and technologies that will disrupt the market in 2026 and beyond.
- Ensure the architectural integrity of our AI systems, prioritizing security, scalability, and efficiency.
- Mentor junior staff and foster a culture of innovation and continuous learning within the engineering department.
- Collaborate with legal and compliance teams to navigate the evolving landscape of AI regulation and ethics.
Qualifications
- Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, or a related field; Ph.D. preferred.
- 10+ years of experience in software engineering, machine learning, or AI product management.
- Proven track record of leading large-scale AI projects from conception to deployment.
- Deep expertise in Python, TensorFlow, PyTorch, and large language models (LLMs).
- Exceptional leadership and communication skills, with the ability to translate complex technical concepts for diverse stakeholders.
- Strong understanding of AI ethics, bias mitigation, and responsible AI practices.