Job Description
Shape the Future of Intelligent Systems
QuantumLeap Systems is at the forefront of the next generation of technology. As we prepare for the rapid advancements of 2026 and beyond, we are seeking a visionary Senior AI Architect to lead the design and deployment of autonomous agents and generative AI infrastructures.
In this role, you won't just be maintaining legacy systems; you will be architecting the foundation for the next decade of human-machine interaction. If you thrive in a high-velocity environment and are obsessed with the convergence of Large Language Models (LLMs) and autonomous decision-making, we want to talk to you.
Why Join Us?
- Impact: Your code will power the AI agents that redefine productivity in enterprise sectors.
- Future-Proofing: Work exclusively on cutting-edge 2026-ready technologies including Agentic Workflows and Multi-modal AI.
- Culture: A meritocratic, diverse team of engineers, researchers, and strategists.
Responsibilities
- Design and implement scalable, distributed AI architectures capable of processing petabytes of real-time data.
- Lead the development of autonomous agent frameworks that leverage LLMs for complex, multi-step reasoning.
- Optimize model inference latency and throughput to support high-volume production environments.
- Collaborate with product teams to define technical roadmaps aligned with 2026 technology trends.
- Establish best practices for MLOps, including model versioning, monitoring, and continuous deployment.
- Conduct rigorous code reviews and mentor junior engineers to foster technical excellence.
Qualifications
- PhD or Master’s degree in Computer Science, Machine Learning, or a related quantitative field.
- 8+ years of experience in software engineering with a strong focus on AI/ML.
- Deep expertise in Python, PyTorch, and TensorFlow, with hands-on experience in deploying models via Kubernetes and Docker.
- Proven track record of architecting systems using Vector Databases and RAG (Retrieval-Augmented Generation) architectures.
- Experience implementing guardrails and safety protocols for Generative AI models.
- Strong understanding of distributed systems, microservices, and cloud-native technologies (AWS/Azure/GCP).