Job Description
Join FutureScale Inc., a leader in next-generation artificial intelligence, as our Senior AI Architect. We are not just building software for today; we are architecting the intelligent systems that will define the landscape of 2026 and beyond. You will lead a team of brilliant engineers in designing scalable, resilient, and ethical AI infrastructures.
In this pivotal role, you will bridge the gap between theoretical AI research and production-grade engineering. If you have a passion for pushing the boundaries of what is possible and a deep understanding of distributed systems, we want to meet you.
Why You'll Love Working Here
- Future-Ready Tech Stack: Work with the latest in LLMs, vector databases, and edge computing.
- Competitive Compensation: $160k - $220k base salary plus equity.
- Impactful Work: Your code will power AI solutions used by millions.
- Remote-First Culture: Flexible work environment with a global team.
Core Responsibilities
- Design and implement scalable AI architectures capable of handling petabyte-scale data.
- Lead the migration of legacy systems to modern, serverless, and edge-computing frameworks.
- Collaborate with data scientists to translate research prototypes into production-ready models.
- Establish best practices for MLOps, ensuring model deployment, monitoring, and retraining pipelines are robust.
- Mentor junior engineers and foster a culture of technical excellence and continuous learning.
- Advocate for ethical AI practices, ensuring transparency and fairness in algorithmic decision-making.
Qualifications
- 10+ years of experience in software engineering, with at least 5 years specifically in AI/ML infrastructure.
- Deep expertise in programming languages such as Python, Java, or C++.
- Strong proficiency with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes).
- Experience with machine learning frameworks (TensorFlow, PyTorch) and orchestration tools (Airflow, Kubeflow).
- Proven track record of leading high-performance engineering teams.
- Excellent problem-solving skills with a focus on scalability and performance optimization.
Responsibilities
- Design and implement scalable AI architectures capable of handling petabyte-scale data.
- Lead the migration of legacy systems to modern, serverless, and edge-computing frameworks.
- Collaborate with data scientists to translate research prototypes into production-ready models.
- Establish best practices for MLOps, ensuring model deployment, monitoring, and retraining pipelines are robust.
- Mentor junior engineers and foster a culture of technical excellence and continuous learning.
- Advocate for ethical AI practices, ensuring transparency and fairness in algorithmic decision-making.
Qualifications
- 10+ years of experience in software engineering, with at least 5 years specifically in AI/ML infrastructure.
- Deep expertise in programming languages such as Python, Java, or C++.
- Strong proficiency with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes).
- Experience with machine learning frameworks (TensorFlow, PyTorch) and orchestration tools (Airflow, Kubeflow).
- Proven track record of leading high-performance engineering teams.
- Excellent problem-solving skills with a focus on scalability and performance optimization.