Job Description
Are you ready to define the future of technology?
Quantum Nexus Solutions is leading the charge in the 2026 Horizon Initiative, a strategic push to revolutionize enterprise AI with autonomous agents and next-gen generative models. We are seeking a visionary Senior AI Architect to design the infrastructure that powers the digital economy of tomorrow.
In this role, you won't just write code; you will architect the cognitive backbone of our platform. You will bridge the gap between theoretical machine learning research and scalable production deployment, ensuring our systems are not only intelligent but also secure and ethical.
Why join the 2026 Horizon team?
- Work on cutting-edge research projects that set industry standards.
- Competitive compensation and equity packages.
- Flexible remote-first culture with top-tier benefits.
Join us in building the AI systems that will define the next decade.
Responsibilities
- Architect Design: Design and implement robust, scalable, and secure AI infrastructure for the 2026 Horizon Initiative, focusing on Large Language Models (LLMs) and Multi-Agent Systems.
- Model Optimization: Lead efforts in model fine-tuning, distillation, and quantization to reduce latency and deployment costs while maintaining high accuracy.
- System Integration: Integrate AI capabilities into existing enterprise ecosystems, ensuring seamless data flow and API interoperability.
- MLOps Implementation: Establish and maintain CI/CD pipelines for machine learning models, utilizing tools like Kubernetes, MLflow, and Docker.
- Ethical AI Oversight: Define and enforce guidelines for AI safety, bias mitigation, and responsible AI deployment.
- Technical Leadership: Mentor a team of junior engineers and data scientists, fostering a culture of innovation and continuous learning.
Qualifications
- Education: Master’s or Ph.D. in Computer Science, Artificial Intelligence, or a related quantitative field.
- Experience: 5+ years of professional experience in AI/ML engineering, with a proven track record of deploying production-grade models.
- Technical Skills: Expert proficiency in Python, PyTorch, or TensorFlow. Deep understanding of distributed systems and cloud architecture (AWS, GCP, or Azure).
- Specialized Knowledge: Strong experience with Generative AI, RAG (Retrieval-Augmented Generation), and vector databases (Pinecone, Milvus).
- Problem Solving: Ability to tackle complex, unstructured problems and translate them into elegant technical solutions.
- Communication: Excellent written and verbal communication skills, capable of explaining complex technical concepts to non-technical stakeholders.