Job Description
We are looking for a visionary Lead AI Architect to define the technological landscape of the future. As part of our 2026 Initiative, you will lead the charge in building scalable, robust, and cutting-edge artificial intelligence systems that will revolutionize our industry.
In this role, you will bridge the gap between theoretical research and practical application, ensuring our AI infrastructure is ready for the demands of tomorrow. You will be responsible for the end-to-end lifecycle of our AI solutions, from prototype to production deployment.
Why join us? We offer competitive compensation, a dynamic work environment, and the opportunity to work on projects that will define the next decade of technology.
Responsibilities
- Architectural Leadership: Design and implement a scalable AI infrastructure and machine learning pipeline aligned with our 2026 strategic roadmap.
- Model Development: Spearhead the research and development of advanced Large Language Models (LLMs) and generative AI applications.
- System Integration: Collaborate with cross-functional teams to seamlessly integrate AI capabilities into our core enterprise software products.
- Performance Optimization: Continuously monitor, optimize, and fine-tune model performance to ensure high accuracy and low latency in production environments.
- MLOps & Governance: Establish best practices for MLOps, data governance, and ethical AI usage to ensure compliance and reliability.
- Talent Mentorship: Guide and mentor a team of data scientists and junior engineers to foster a culture of innovation and technical excellence.
Qualifications
- Education: Master’s or PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related technical field.
- Experience: 8+ years of professional experience in software engineering and machine learning architecture.
- Technical Skills: Expert proficiency in Python, PyTorch, or TensorFlow.
- Cloud Expertise: Proven experience deploying and managing AI models in major cloud platforms (AWS, GCP, or Azure).
- System Design: Strong understanding of distributed systems, microservices, and cloud architecture patterns.
- Problem Solving: Demonstrated ability to tackle complex technical challenges and translate them into elegant, scalable solutions.
- Communication: Excellent verbal and written communication skills with the ability to present complex technical concepts to non-technical stakeholders.