GenAI Engineer

Please see the high-level pointers:

• Proficiency in cloud-native architectures and services on both Azure and AWS.
• Track record of leading end-to-end delivery of generative AI projects or AI-powered platforms, Databricks.
• Ability to translate business requirements into technical solutions and manage delivery timelines.
• Experience coordinating cross-functional teams including developers, cloud engineers, and possibly data scientists.
• Experience mentoring and providing technical guidance to developers and engineers.
• Knowledge of cloud security best practices, identity and access management, and data privacy considerations relevant to AI workloads.
• Ability to troubleshoot complex technical issues related to AI model deployment and cloud infrastructure.

Education and Experience:

• Degree/Master's in Computer Science, Information Technology, Computer Engineering, or equivalent.

• Minimum of 10 years of experience in data analytics, with at least 5 years in a management role managing large-scale data analytics projects.

• Proven experience with AWS cloud services, including setting up and managing cloud infrastructure, and deep expertise in Databricks Lakehouse and AI/ML technologies.

Technical Skills:

• Design, develop, and implement GenAI solutions that integrate with Azure and OpenAI platforms.

• Conduct research and stay up-to-date with the latest advancements in GenAI, Azure, OpenAI, AWS, and Google GenAI technologies.

* Experience with AWS services, such as Amazon SageMaker, AWS Lambda, and AWS AI/ML services.

* Knowledge of Google Cloud services, including Google Cloud AI Platform, Google Cloud Functions, and Google Cloud AutoML.

* Experience with cloud-based deployment and scaling of GenAI applications on Azure, AWS, and Google Cloud.

• Proficiency in databases (e.g., Oracle, MS SQL, MySQL, Teradata, Databricks), data repositories (e.g., data lakes, data marts).

• Experience in data modelling, data transformation, and statistical computing (e.g., R, Python).

• Deep understanding of machine learning (MLOps), data visualization (e.g., Power BI, Tableau), and event-driven architecture.

• Expertise in cloud-native technologies and services, including microservices, serverless computing, and containerization (e.g., Docker, Kubernetes).

• Strong knowledge of cloud data platforms, including architecture design, data integration, and the implementation of scalable data pipelines.

Leadership and Management Skills:

• Strong leadership abilities with a track record of managing high performing teams and complex projects.

• Excellent program and project management skills, including the ability to prioritize tasks, manage resources, and meet deadlines.

• Strong interpersonal and communication skills, with the ability to engage and influence stakeholders at all levels.

Certifications:

• AWS Cloud Practitioner or AWS Architect certification.

• Databricks Certified Data Engineer Associate or Professional certificate a plus.

• Project Management Professional (PMP) or similar certification is highly desirable.

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