Job Description
We are pioneering the autonomous systems of tomorrow. As the landscape of technology accelerates toward 2026, we are seeking a visionary Autonomous AI Architect to lead our next-generation research division.
In this pivotal role, you will be responsible for designing and deploying self-correcting, multi-agent AI systems capable of complex reasoning and autonomous decision-making. You will bridge the gap between theoretical AI research and scalable production infrastructure, ensuring our systems are safe, ethical, and capable of outperforming current benchmarks.
If you are obsessed with the future of Artificial General Intelligence (AGI) and want to build the foundational models that will define the next era of human-machine collaboration, apply today.
Responsibilities
- Architect Agentic Workflows: Design and implement complex, multi-agent orchestration frameworks that enable AI systems to plan, execute, and self-correct without human intervention.
- Model Optimization: Fine-tune and optimize Large Language Models (LLMs) for high-stakes decision-making, focusing on reasoning accuracy and latency reduction.
- R&D Leadership: Lead internal research initiatives exploring novel architectures for 2026-era AI capabilities, including memory-augmented networks and world modeling.
- System Integration: Integrate disparate data sources and tools into autonomous AI agents, creating a seamless 'digital workforce' for enterprise clients.
- Ethical Alignment: Develop and enforce guardrails to ensure AI behavior remains safe, unbiased, and aligned with human values.
- Technical Mentorship: Mentor a team of junior data scientists and ML engineers, fostering a culture of innovation and technical excellence.
Qualifications
- Education: Master’s degree or PhD in Computer Science, Artificial Intelligence, or a related quantitative field.
- Experience: 7+ years of experience in machine learning, deep learning, or AI research, with at least 2 years specifically in Agentic AI or LLM application development.
- Technical Proficiency: Expert-level knowledge of Python, PyTorch, and TensorFlow. Experience with LangChain, LlamaIndex, or similar orchestration frameworks.
- Infrastructure: Strong background in cloud architecture (AWS/GCP/Azure) and containerization (Docker, Kubernetes) for deploying scalable AI models.
- Mathematics: Deep understanding of linear algebra, probability, and statistics required for advanced model optimization.
- Communication: Exceptional ability to translate complex technical concepts into clear, actionable insights for cross-functional teams.