Cloud and AI Sales Engineer

Job Summary

The Cloud and AI Sales Engineer role at Cloudvests involves bridging commercial strategy with technical execution to drive revenue growth in cloud and AI solutions. The position requires engaging with clients on both business and technical levels to support sales of AWS-based services.

Responsibilities

• Manage the entire sales cycle by identifying, qualifying, and closing opportunities related to AWS cloud migrations, modernization, and AI/ML projects.
• Serve as the initial technical consultant for potential clients, identifying their challenges and aligning them with AWS solutions such as Amazon Bedrock, SageMaker, EC2, S3, and Lambda.
• Prepare proposals, pitch presentations, and Total Cost of Ownership analyses to demonstrate the value of Cloudvests’ offerings.
• Work closely with AWS Solutions Architects and Delivery Teams to create precise Statements of Work and ensure smooth project transitions.
• Lead technical demonstrations and coordinate Proof of Concept activities for Generative AI and data analytics solutions.
• Represent Cloudvests at industry events, webinars, and AWS community meetups to enhance brand presence and generate leads.

Must haves

• At least 3 years of experience in B2B technology sales, account executive, or sales engineering roles with a technical background such as a degree in Computer Science or Engineering, or prior development/engineering experience.
• Strong understanding of cloud computing concepts and the AWS ecosystem, including knowledge of IaaS, PaaS, SaaS, and cloud migration strategies.
• Excellent presentation and communication skills with experience influencing C-level and technical stakeholders.
• Proven capability to manage complex sales processes involving multiple stakeholders from discovery through closing.

Nice to haves

• Current AWS certifications like AWS Certified Cloud Practitioner or AWS Certified Solutions Architect – Associate.
• Experience working at or with an AWS Partner or Systems Integrator.
• Knowledge of modern data strategies including data lakes, pipelines, and analytics.

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