Job Description
Shape the Future of Intelligence
Nexus Future Systems is pioneering the 2026 AI landscape. We are looking for a visionary Lead AI Architect to lead the development of next-generation Generative AI and Autonomous Agent frameworks. This is not just about deploying models; it is about architecting the cognitive infrastructure of tomorrow.
As part of our elite engineering team, you will bridge the gap between theoretical AI research and production-grade systems, ensuring our solutions are scalable, secure, and ethically grounded.
Responsibilities
- Architect GenAI Pipelines: Design and implement end-to-end large language model (LLM) infrastructure, including model selection, fine-tuning, and deployment strategies for the 2026 roadmap.
- Build Autonomous Agents: Develop intelligent agents capable of complex decision-making, multi-step reasoning, and tool usage in dynamic environments.
- Optimize Performance: Engineer high-performance inference systems, reducing latency and optimizing resource utilization for production workloads.
- RAG & Vector Search: Lead the implementation of advanced Retrieval-Augmented Generation architectures to enhance model accuracy and context awareness.
- Evaluate & Iterate: Establish rigorous evaluation frameworks (LLM-as-a-judge) to continuously measure and improve model outputs against business KPIs.
- Collaborate Cross-Functionally: Partner with product managers, data scientists, and security teams to integrate AI solutions seamlessly into our products.
Qualifications
- Education: Master’s or PhD in Computer Science, Mathematics, or a related technical field.
- Experience: 5+ years of professional experience in Machine Learning Engineering, with at least 2 years focused on Generative AI or LLMs.
- Technical Proficiency: Deep expertise in Python, PyTorch, TensorFlow, and Hugging Face Transformers.
- LLM Knowledge: Proven experience fine-tuning open-source models (Llama 3, Mistral) or working with proprietary APIs (OpenAI, Anthropic).
- System Design: Strong understanding of distributed systems, cloud architecture (AWS/Azure/GCP), and MLOps best practices.
- Soft Skills: Exceptional problem-solving abilities and the ability to communicate complex technical concepts to non-technical stakeholders.