Job Description
Are you ready to architect the future of intelligence?
Nexus Future Systems is at the forefront of the technological revolution, building the foundational infrastructure for the year 2026 and beyond. We are seeking a visionary Future Tech Lead to spearhead our Generative AI and Large Language Model (LLM) initiatives. This is not just a job; it is a mission to redefine human-machine interaction.
In this role, you will bridge the gap between theoretical AI breakthroughs and scalable, enterprise-grade software solutions. If you are passionate about the trajectory of technology and want to leave a lasting impact on the digital landscape, we want to hear from you.
Responsibilities
- Architect 2026-Ready AI Solutions: Design and implement scalable Large Language Model (LLM) architectures that anticipate future data trends and user behaviors.
- Lead Generative AI Strategy: Oversee the integration of Generative AI across product lines, ensuring ethical, safe, and high-performance outputs.
- Model Optimization & Training: Lead the training pipelines for proprietary models, focusing on fine-tuning for specific industry verticals and reducing inference costs.
- Technical Roadmap Development: Define the technical vision and roadmap for AI capabilities, ensuring alignment with business goals and emerging industry standards.
- Cross-Functional Collaboration: Partner with engineering, product, and design teams to translate complex AI concepts into user-centric features.
- Mentorship & Culture: Foster a culture of innovation and continuous learning within the engineering team, mentoring junior data scientists and AI engineers.
- Research & Innovation: Stay ahead of the curve by evaluating new research papers, frameworks, and breakthrough technologies relevant to the 2026 tech ecosystem.
Qualifications
- Experience: 8+ years of experience in software engineering, with at least 4 years specializing in Artificial Intelligence, Machine Learning, or Deep Learning.
- Technical Expertise: Profound knowledge of Python, PyTorch, TensorFlow, and Hugging Face ecosystems. Experience with distributed training and model serving (e.g., Kubernetes, Ray).
- AI Mastery: Deep understanding of NLP, Transformer architectures, and prompt engineering principles.
- Leadership: Demonstrated ability to lead technical teams, manage complex projects, and drive strategic initiatives from conception to deployment.
- Education: Master’s degree or PhD in Computer Science, Artificial Intelligence, or a related technical field is highly preferred.
- Problem Solving: Exceptional analytical skills with a track record of solving ambiguous, high-impact technical problems.
- Communication: Ability to communicate complex technical concepts to non-technical stakeholders effectively.