Job Description
We are seeking a visionary 2026 AI Strategy Lead to spearhead our flagship '2026' initiative. At Horizon Nexus Corp, we are not just predicting the future; we are architecting it. In this role, you will define the roadmap for our next-generation artificial intelligence systems, bridging the gap between theoretical AI research and scalable, real-world enterprise solutions.
You will be at the forefront of technological innovation, working with a world-class team to build the infrastructure that will define the next decade of human-computer interaction. If you are passionate about pushing the boundaries of what is possible with machine learning and want to leave a lasting impact on the industry, we want to hear from you.
Key Areas of Focus:
- Defining the technical and strategic vision for the '2026' product suite.
- Overseeing the integration of Large Language Models (LLMs) into core business workflows.
- Ensuring ethical AI development and compliance with global standards.
Responsibilities
- Strategic Planning: Develop and communicate a comprehensive AI strategy for the 2026 initiative, ensuring alignment with company goals and market trends.
- Technical Leadership: Architect scalable AI solutions that can handle massive data volumes while maintaining low latency.
- R&D Leadership: Guide a team of data scientists and ML engineers in exploring cutting-edge algorithms and model training techniques.
- Stakeholder Management: Translate complex technical concepts into clear insights for executives and non-technical stakeholders.
- Performance Optimization: Continuously monitor, evaluate, and improve the performance and accuracy of deployed AI models.
- Innovation Management: Stay ahead of industry trends, including generative AI and autonomous systems, to keep Horizon Nexus at the cutting edge.
Qualifications
- Experience: 10+ years in software engineering or data science, with at least 5 years in a leadership or strategic role.
- Education: Master’s degree or PhD in Computer Science, Artificial Intelligence, or a related quantitative field.
- Technical Expertise: Deep understanding of machine learning frameworks (TensorFlow, PyTorch), NLP, and deep learning architectures.
- Programming: Proficiency in Python, Java, or C++ with experience in big data technologies (Spark, Kafka).
- Leadership: Proven track record of leading high-performance teams and managing cross-functional projects.
- Problem Solving: Exceptional analytical skills with a focus on solving complex, unstructured problems.