Mandatory
- 12+ years of hands-on technical experience in software engineering, with at least 5+ years in a leadership role managing cross-functional teams, including GenAI, machine learning, and cloud infrastructure.
- Hands-on Experience in designing and developing large-scale systems, including GenAI, API architectures, data systems, ML pipelines, and cloud-native applications.
- Programming Languages: Proficiency in Python, JavaScript, Java, or other backend languages. Experience with API development (RESTful APIs, GraphQL).
- Machine Learning & AI: Extensive experience in building and deploying ML models using TensorFlow, PyTorch, scikit-learn, and spaCy, with hands-on experience in integrating them into GenAI applications.
Preferred:
Hands on experience in GCP/Data Engineering/DevOps
Detailed Jd:
The AI architect will play a pivotal role in architecting, leading, and actively contributing to the development of GenAI applications, machine learning models, data engineering pipelines, and cloud-native infrastructure. This hands-on leadership position requires extensive technical expertise and experience in managing a diverse, cross-functional team of engineers spanning GenAI App Development, Data Science, Machine Learning, Full Stack, DevOps, Cloud Infrastructure, and API development.
Be responsible for architecting complex systems, making critical decisions, and leading teams to deliver high-quality, scalable solutions while remaining directly involved in coding, technical design, and problem-solving.