- Define and execute the companys technology vision architecture and strategy aligned with business goals.
- Lead end-to-end AI product development from data engineering to deployment.
- Oversee data infrastructure pipelines and cloud architecture to support large-scale analytics and machine learning workloads.
- Collaborate with cross-functional teams (Product Engineering and Business) to integrate AI into core products and business processes.
- Stay ahead of industry trends in AI ML LLMs and Generative AI and translate them into actionable innovation.
- Build and mentor a high-performing engineering and AI team.
- Establish and maintain best practices for software development DevOps MLOps and data governance.
- Manage technology budgets vendor relationships and ensure scalable secure and efficient systems.
Requirements
- Strong foundation in software development (Python Java or similar).
- Deep expertise in Data Engineering ETL Data Warehousing and Big Data tools (e.g. Spark Databricks Airflow ADF).
- Proven experience in AI/ML model development LLMs NLP and Neural Networks.
- Hands-on with cloud platforms (Azure / AWS / GCP) and MLOps pipelines.
- Understanding of modern architectures microservices APIs event-driven systems and containerization (Docker Kubernetes).
- Excellent leadership communication and strategic planning skills.
- Prior experience scaling technology in startups or enterprise environments is a strong plus.
Required Skills:
AIML
Define and execute the companys technology vision architecture and strategy aligned with business goals.Lead end-to-end AI product development from data engineering to deployment.Oversee data infrastructure pipelines and cloud architecture to support large-scale analytics and machine learning worklo...
- Define and execute the companys technology vision architecture and strategy aligned with business goals.
- Lead end-to-end AI product development from data engineering to deployment.
- Oversee data infrastructure pipelines and cloud architecture to support large-scale analytics and machine learning workloads.
- Collaborate with cross-functional teams (Product Engineering and Business) to integrate AI into core products and business processes.
- Stay ahead of industry trends in AI ML LLMs and Generative AI and translate them into actionable innovation.
- Build and mentor a high-performing engineering and AI team.
- Establish and maintain best practices for software development DevOps MLOps and data governance.
- Manage technology budgets vendor relationships and ensure scalable secure and efficient systems.
Requirements
- Strong foundation in software development (Python Java or similar).
- Deep expertise in Data Engineering ETL Data Warehousing and Big Data tools (e.g. Spark Databricks Airflow ADF).
- Proven experience in AI/ML model development LLMs NLP and Neural Networks.
- Hands-on with cloud platforms (Azure / AWS / GCP) and MLOps pipelines.
- Understanding of modern architectures microservices APIs event-driven systems and containerization (Docker Kubernetes).
- Excellent leadership communication and strategic planning skills.
- Prior experience scaling technology in startups or enterprise environments is a strong plus.
Required Skills:
AIML
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