Job Description
We are on the precipice of a technological revolution. Nexus Horizon AI is seeking a visionary Lead AI Architect to define the infrastructure for the next generation of Generative AI systems.
As we look toward 2026, the industry is shifting from static models to autonomous, agentic AI agents. You will be responsible for architecting scalable, secure, and high-performance systems that power the next wave of intelligent applications. If you are a technologist who wants to build the future, this is your stage.
Why join us?
- Work with state-of-the-art LLMs and multimodal architectures.
- Shape the roadmap for AI adoption in enterprise solutions.
- Competitive compensation package and equity options.
Responsibilities
- Architect LLM Solutions: Design and implement scalable infrastructure for Large Language Models and multimodal AI systems.
- Optimize Performance: Fine-tune models for specific domains, ensuring low latency and high throughput in production environments.
- Lead Research & Development: Spearhead internal research into emerging AI paradigms, specifically focusing on Agentic AI and Autonomous Systems for 2026.
- Collaborate Across Teams: Partner with product, engineering, and security teams to integrate AI capabilities seamlessly.
- Establish Best Practices: Define MLOps pipelines, data governance protocols, and ethical AI guidelines.
- Technical Mentorship: Mentor junior engineers and data scientists, fostering a culture of innovation and continuous learning.
Qualifications
- Education: Master’s degree in Computer Science, Machine Learning, or a related field (PhD preferred).
- Programming: Expert proficiency in Python, PyTorch, or TensorFlow.
- Experience: 7+ years of experience in AI/ML engineering, with at least 3 years in a lead or architect role.
- Frameworks: Deep understanding of Hugging Face, LangChain, and vector databases (Pinecone, Weaviate).
- Cloud Native: Strong experience with AWS, GCP, or Azure, specifically in deploying ML workloads.
- Problem Solving: Proven track record of solving complex, unstructured problems using data-driven approaches.
- Communication: Exceptional ability to translate complex technical concepts for diverse stakeholders.