Job Description
We are on a mission to define the technological landscape of 2026. Quantum Horizon Labs is seeking a visionary Senior AI Systems Architect to lead the development of next-generation Autonomous Agent frameworks. You will be at the forefront of integrating Large Language Models (LLMs) with real-time decision-making systems, building the infrastructure that powers the future of enterprise automation.
Why This Role is Special
Unlike traditional software engineering, this position requires a blend of deep learning expertise and high-scale distributed systems architecture. You will not just be writing code; you will be architecting the cognitive layer of our products for the year 2026 and beyond.
Key Responsibilities
- Design and implement scalable, fault-tolerant architectures for Agentic AI workflows, ensuring seamless human-AI collaboration.
- Optimize inference latency and model throughput for real-time decision-making systems using edge computing and serverless architectures.
- Lead the technical strategy for integrating multimodal AI capabilities (text, vision, audio) into a unified 2026-ready platform.
- Establish best practices for AI safety, ethics, and alignment, ensuring robust guardrails against hallucinations and adversarial attacks.
- Collaborate with cross-functional teams of data scientists, product managers, and security engineers to translate research prototypes into production-grade software.
- Drive the migration of legacy monoliths to microservices architectures powered by containerization (Docker/Kubernetes) and serverless functions.
Qualifications
- Master’s degree or PhD in Computer Science, Machine Learning, or a related quantitative field.
- 8+ years of professional experience in software engineering, with at least 3 years specifically focused on AI/ML systems design.
- Deep expertise in Python, C++, and Rust, with proven experience deploying models in production environments.
- Extensive knowledge of Deep Learning frameworks such as PyTorch, TensorFlow, or JAX.
- Experience with cloud platforms (AWS, GCP, or Azure) and infrastructure as code (Terraform).
- Strong understanding of distributed systems principles, including consistency models, caching strategies, and event-driven architectures.
- Exceptional problem-solving skills and the ability to thrive in a fast-paced, experimental R&D environment.
Join us in shaping the future of intelligence.
Responsibilities
- Design scalable, fault-tolerant architectures for Agentic AI workflows, ensuring seamless human-AI collaboration.
- Optimize inference latency and model throughput for real-time decision-making systems using edge computing and serverless architectures.
- Lead the technical strategy for integrating multimodal AI capabilities (text, vision, audio) into a unified 2026-ready platform.
- Establish best practices for AI safety, ethics, and alignment, ensuring robust guardrails against hallucinations and adversarial attacks.
- Collaborate with cross-functional teams of data scientists, product managers, and security engineers to translate research prototypes into production-grade software.
- Drive the migration of legacy monoliths to microservices architectures powered by containerization (Docker/Kubernetes) and serverless functions.
Qualifications
- Master’s degree or PhD in Computer Science, Machine Learning, or a related quantitative field.
- 8+ years of professional experience in software engineering, with at least 3 years specifically focused on AI/ML systems design.
- Deep expertise in Python, C++, and Rust, with proven experience deploying models in production environments.
- Extensive knowledge of Deep Learning frameworks such as PyTorch, TensorFlow, or JAX.
- Experience with cloud platforms (AWS, GCP, or Azure) and infrastructure as code (Terraform).
- Strong understanding of distributed systems principles, including consistency models, caching strategies, and event-driven architectures.
- Exceptional problem-solving skills and the ability to thrive in a fast-paced, experimental R&D environment.