Job Description
Are you ready to engineer the intelligence of tomorrow?
Quantum Horizon Systems is seeking a visionary Lead AI Architect to spearhead the development of autonomous, agentic AI systems designed for the year 2026 and beyond. In this pivotal role, you will build the foundational frameworks for self-improving artificial intelligence that will redefine human-machine interaction.
We are not just building software; we are architecting the future of autonomous decision-making. If you are passionate about pushing the boundaries of Large Language Models (LLMs), multi-agent systems, and ethical AI alignment, this is your chance to lead the charge.
Responsibilities
- Architect Agentic Workflows: Design scalable, end-to-end architectures for autonomous AI agents capable of complex, multi-step reasoning and self-correction without human intervention.
- Model Optimization: Lead the optimization and fine-tuning of proprietary LLMs to ensure high performance, low latency, and enhanced safety in production environments.
- System Integration: Integrate AI agents into broader software ecosystems, ensuring seamless interoperability with legacy systems and modern cloud infrastructure.
- R&D Leadership: Conduct cutting-edge research into emerging AI paradigms, including reinforcement learning, causal inference, and predictive modeling.
- Team Mentorship: Guide a team of senior engineers and data scientists, fostering a culture of innovation and technical excellence.
- AI Safety & Ethics: Implement rigorous guardrails and ethical constraints to ensure AI outputs are responsible, unbiased, and aligned with human values.
Qualifications
- Education: Master’s degree or PhD in Computer Science, Machine Learning, or a related technical field.
- Experience: 8+ years of experience in software engineering with a focus on AI/ML, including at least 3 years in a leadership or architectural role.
- Technical Proficiency: Deep expertise in Python, C++, and frameworks such as PyTorch, TensorFlow, or JAX.
- AI Specialization: Proven experience with LLMs, RAG (Retrieval-Augmented Generation), and the development of agentic systems.
- Cloud Mastery: Strong experience deploying and managing AI workloads on AWS, GCP, or Azure.
- Problem Solving: Demonstrated ability to tackle ambiguous, high-complexity technical challenges and deliver scalable solutions.