Job Description
We are looking for a visionary Lead Agentic AI Engineer to architect the intelligence of 2026 and beyond. At QuantumLeap AI, we are building the autonomous systems that will define the next decade of human-machine collaboration. You won't just be maintaining models; you will be evolving them. In this role, you will lead a high-performance team in designing self-improving agents capable of complex reasoning, multi-step planning, and seamless integration into enterprise workflows. This is a rare opportunity to shape the foundational technology of the future.
Responsibilities
- Architect and deploy scalable, autonomous AI agents using advanced LLMs and Reinforcement Learning.
- Drive the R&D strategy for next-generation Natural Language Processing (NLP) and multimodal systems.
- Optimize model inference latency and throughput to support real-time, high-volume applications.
- Collaborate cross-functionally to integrate '2026 Vision' features into our core product ecosystem.
- Mentor junior engineers and establish best practices for AI safety, alignment, and ethical deployment.
- Conduct rigorous testing and evaluation of agent autonomy, hallucination reduction, and reliability.
- Manage the full ML lifecycle from experimentation to production deployment using MLOps best practices.
Qualifications
- PhD or Master’s degree in Computer Science, Artificial Intelligence, or a related technical field.
- 5+ years of professional experience in Machine Learning Engineering or Applied AI research.
- Deep expertise in Python, PyTorch, TensorFlow, and modern ML frameworks.
- Proven track record of deploying large-scale LLM applications (e.g., RAG systems, agents via LangChain/LlamaIndex).
- Strong understanding of vector databases, embeddings, and semantic search architectures.
- Experience with cloud infrastructure (AWS, GCP, or Azure) and containerization (Docker/Kubernetes).
- Excellent communication skills with the ability to translate technical concepts for non-technical stakeholders.