Job Description
We are at the forefront of the 2026 AI revolution, building the next generation of autonomous agents and generative intelligence systems. At QuantumLeap Dynamics, we are looking for a visionary Senior AI Infrastructure Engineer to architect the scalable, secure, and resilient backend systems that power our proprietary models.
If you are passionate about deploying LLMs at scale, optimizing neural network training pipelines, and ensuring zero-latency inference across edge and cloud environments, this is your opportunity to lead the charge into the future.
Key Responsibilities:
- Architect and maintain high-availability distributed systems designed for machine learning workloads.
- Optimize data pipelines for the training and fine-tuning of large language models and multi-modal agents.
- Collaborate closely with ML researchers to deploy production-ready models with sub-millisecond latency.
- Implement rigorous security protocols and data governance frameworks for sensitive AI operations.
- Establish and mentor engineering best practices for scalability and observability.
Qualifications:
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field.
- 5+ years of experience in backend engineering with a strong focus on Python, Go, or Rust.
- Deep expertise in containerization (Docker/Kubernetes) and cloud infrastructure (AWS/GCP/Azure).
- Experience with vector databases, semantic search, and real-time inference engines.
- Strong problem-solving skills with a proven track record of delivering complex technical solutions.
Responsibilities
- Architect and maintain high-availability distributed systems designed for machine learning workloads.
- Optimize data pipelines for the training and fine-tuning of large language models and multi-modal agents.
- Collaborate closely with ML researchers to deploy production-ready models with sub-millisecond latency.
- Implement rigorous security protocols and data governance frameworks for sensitive AI operations.
- Establish and mentor engineering best practices for scalability and observability.
Qualifications
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field.
- 5+ years of experience in backend engineering with a strong focus on Python, Go, or Rust.
- Deep expertise in containerization (Docker/Kubernetes) and cloud infrastructure (AWS/GCP/Azure).
- Experience with vector databases, semantic search, and real-time inference engines.
- Strong problem-solving skills with a proven track record of delivering complex technical solutions.