Job Description
The Opportunity
Nexus Future Systems is pioneering the next generation of artificial intelligence, and we are seeking a visionary Lead AI Architect to spearhead our Project 2026 initiative. As we prepare to deploy autonomous agents and generative AI systems at scale, you will define the architectural blueprint that powers our ecosystem.
We are looking for a technical leader who is not just comfortable with the technology of today, but is actively building the foundation for the enterprise AI landscape of 2026.
Why Join Us?
- Shape the roadmap for the year 2026.
- Work with state-of-the-art Large Language Models (LLMs) and generative AI.
- Competitive compensation and equity package.
Key Responsibilities
- Design and implement scalable, high-performance AI architectures for the 2026 platform.
- Lead a cross-functional team of ML engineers, data scientists, and researchers.
- Optimize model inference latency and resource utilization for edge and cloud environments.
- Establish best practices for MLOps, data governance, and ethical AI usage.
- Collaborate with stakeholders to translate business requirements into technical AI solutions.
Qualifications
- Master’s degree or PhD in Computer Science, Machine Learning, or a related technical field.
- 8+ years of experience in Software Engineering and 4+ years specifically in AI/ML architecture.
- Deep expertise in Python, PyTorch, TensorFlow, or JAX.
- Proven track record of deploying production-grade LLMs and NLP models.
- Strong understanding of distributed systems, microservices, and cloud infrastructure (AWS/GCP).
- Experience in mentoring engineering teams and driving technical strategy.
Skills
Python, PyTorch, TensorFlow, AWS, GCP, Docker, Kubernetes, MLOps, LLMs, NLP, Generative AI, Machine Learning Engineering, System Design.
Responsibilities
- Design and implement scalable, high-performance AI architectures for the 2026 platform.
- Lead a cross-functional team of ML engineers, data scientists, and researchers.
- Optimize model inference latency and resource utilization for edge and cloud environments.
- Establish best practices for MLOps, data governance, and ethical AI usage.
- Collaborate with stakeholders to translate business requirements into technical AI solutions.
Qualifications
- Master’s degree or PhD in Computer Science, Machine Learning, or a related technical field.
- 8+ years of experience in Software Engineering and 4+ years specifically in AI/ML architecture.
- Deep expertise in Python, PyTorch, TensorFlow, or JAX.
- Proven track record of deploying production-grade LLMs and NLP models.
- Strong understanding of distributed systems, microservices, and cloud infrastructure (AWS/GCP).
- Experience in mentoring engineering teams and driving technical strategy.