Job Description
Are you ready to define the technological landscape of 2026?
Apex Future Systems is at the forefront of innovation, building the next generation of neural architectures and scalable cloud ecosystems. We are seeking a visionary Senior AI Infrastructure Architect to lead our engineering team in designing resilient, high-performance systems for the future.
In this role, you will bridge the gap between cutting-edge Artificial Intelligence research and robust, production-grade infrastructure. You will be instrumental in preparing our systems for the challenges of the 2026 era, ensuring we remain agile, secure, and ahead of the curve.
Why join us?
- Work on mission-critical projects that shape the future of industry.
- Competitive compensation package with equity options.
- Flexible remote-first policy with a premium office in the heart of SF.
- Access to state-of-the-art hardware and AI research labs.
Responsibilities
- Architect and deploy scalable AI infrastructure solutions that support next-generation deep learning models and generative AI workloads.
- Lead the migration and optimization of legacy systems to modern, serverless cloud architectures (AWS/Azure/GCP).
- Design high-availability systems capable of handling petabyte-scale data processing with sub-millisecond latency.
- Collaborate with data science and ML engineering teams to streamline model training and deployment pipelines (MLOps).
- Establish and enforce best practices for cloud security, data governance, and ethical AI implementation.
- Drive technical roadmaps for the 2026 infrastructure evolution, evaluating emerging technologies like quantum-ready cloud services.
Qualifications
- 10+ years of experience in software engineering, DevOps, or Cloud Architecture with at least 5 years specifically in AI/ML infrastructure.
- Deep expertise in designing and managing large-scale distributed systems using Kubernetes, Docker, and microservices.
- Proficiency in programming languages such as Python, Go, or Java, with strong understanding of systems programming.
- Hands-on experience with major cloud providers and their AI/ML services (e.g., SageMaker, Vertex AI, GKE).
- Strong background in MLOps tools (MLflow, Kubeflow, Airflow) and CI/CD pipelines.
- Bachelor’s degree in Computer Science, Engineering, or a related field; Master’s degree or PhD preferred.