Job Description
The year 2026 is approaching, and we are on the cusp of a technological revolution. At Quantum Leap Systems, we are not just preparing for the future; we are architecting it. We are seeking a visionary Senior Agentic AI Engineer to lead our initiative in building autonomous, self-improving systems that will define the next era of enterprise intelligence.
As AI transitions from reactive tools to proactive agents, the demand for sophisticated architectures is unprecedented. This role offers the unique opportunity to shape the trajectory of technology for 2026, working with state-of-the-art models and cutting-edge infrastructure.
Why Join Us?
- Be a Pioneer: Work on the frontier of Agentic AI and autonomous decision-making systems.
- Impact Scale: Deploy solutions that will be used by millions, setting the standard for the industry.
- Competitive Compensation: Base salary plus performance-based equity.
Responsibilities
- Architect Intelligent Agents: Design and deploy scalable autonomous AI agents capable of complex, multi-step reasoning and independent decision-making workflows.
- LLM Integration: Lead the integration of Large Language Models (LLMs) into production environments using Retrieval-Augmented Generation (RAG) and fine-tuning techniques.
- System Optimization: Engineer high-performance inference pipelines, optimizing for speed and cost in cloud-based environments.
- Research & Development: Conduct deep research into emerging paradigms such as Multi-Agent Systems, reinforcement learning, and human-in-the-loop feedback loops.
- Collaboration: Partner with product and engineering teams to translate complex AI capabilities into user-friendly applications.
Qualifications
- Education: Master’s or PhD in Computer Science, Mathematics, Statistics, or a related technical field.
- Experience: Minimum of 5+ years of professional experience in Machine Learning, Deep Learning, or Natural Language Processing.
- Technical Skills: Expert proficiency in Python, PyTorch, or TensorFlow; strong understanding of transformer architectures and large language model mechanics.
- Infrastructure: Proven experience with cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).
- Problem Solving: Demonstrated ability to tackle ambiguous problems and deliver innovative technical solutions.
- Communication: Excellent verbal and written communication skills for technical documentation and stakeholder presentations.