Mimecast is seeking to solve the problem of AI transformation and implementation of AI Business initiatives within the organization, focusing on driving innovation, enhancing operational efficiency, and fostering a culture of data-driven decision-making.
Requirements
- Proficiency in programming languages such as SQL, Python, or R
- Experience with AI/ML frameworks (e.g., TensorFlow, PyTorch)
- Familiarity with cloud platforms (e.g., AWS, Azure, Google Cloud)
- Familiarity with cloud data platforms (e.g Snowflake, dbt, Fivetran)
- Strong understanding of data architecture, data pipelines, and ETL processes
- Experience with Generative AI and related technologies, a plus (eg. AWS Bedrock, Pinecone, OpenSearch, etc)
- Experience with AI tools, platforms, and frameworks
Responsibilities
- Assess & Recommend AI Tools: Evaluate and recommend AI tools, platforms, and frameworks, balancing the decision between building in-house solutions versus purchasing existing technologies.
- Data Pipeline & AI Architecture: Design and implement robust data pipelines that support the development and deployment of AI models, ensuring efficient data flow and accessibility.
- Collaboration with AI & Data Science Teams: Partner with AI and data science teams to align on project goals, share insights, and drive innovation in AI Transformation.
- Collaboration with Data Engineers and IT: Work closely with data engineers and IT teams to ensure seamless integration and proper data flow across systems, facilitating effective AI model training and deployment.
- AI Infrastructure Deployment & Scaling: Oversee the deployment and scaling of AI infrastructure to support ongoing and future AI initiatives, ensuring high availability and performance.
- Performance Monitoring: Establish and maintain performance monitoring systems for AI models, ensuring they meet operational standards and continuously improve based on feedback and data analysis
- AI Literacy: Collaborate with the team on championing AI Literacy at Mimecast using AI to achieve outsized returns in revenue and operational efficiency
Other
- Educational Background: BA/BS in Computer Science, Data Science, Engineering, or a related field.
- Experience: Minimum of 5 years of experience in AI/ML and data engineering, with a strong focus on business value and increasing responsibility in leadership roles
- Leadership Abilities: Proven track record of leading cross-functional teams and managing complex projects in a fast-paced environment.
- Analytical Mindset: Strong analytical and problem-solving skills, with the ability to interpret complex data and make data-driven decisions.
- Communication Skills: Excellent verbal and written communication skills, with the ability to convey technical concepts to non-technical stakeholders.
