Cloud and AI Sales Engineer

About the role

Cloudvests, an AWS Advanced Partner, delivers cloud infrastructure and artificial intelligence solutions to businesses and is looking for a Cloud and AI Sales Engineer. The role bridges commercial strategy and technical execution and drives revenue growth across the Cloud and AI portfolios. It suits a sales professional with a strong technical background who is comfortable negotiating contracts and explaining cloud architecture, machine learning models and AWS infrastructure to CTOs and engineering leads.

Key responsibilities

• Drive full-cycle sales: prospect, qualify and close new business for AWS cloud migrations, modernization projects and AI/ML initiatives.
• Lead technical discovery: act as the first line of technical consultation and map client challenges to AWS solutions such as Amazon Bedrock, SageMaker, EC2, S3 and Lambda.
• Develop proposals and ROI cases, including pitch decks and Total Cost of Ownership (TCO) analyses.
• Partner with AWS Solutions Architects and delivery teams to design accurate Statements of Work (SOWs) and ensure smooth project handoffs.
• Deliver demos and coordinate Proof of Concept (PoC) engagements for GenAI and data analytics solutions.
• Represent the company at industry events, webinars and AWS ecosystem meetups to build pipeline and brand awareness.

Required profile

• 3+ years of experience in B2B tech sales, account executive or sales engineering roles, with a technical background (e.g. a degree in Computer Science or Engineering, or prior hands-on experience as a developer or engineer).
• Proven ability to influence C-level executives and technical stakeholders.
• Demonstrated ability to manage complex, multi-stakeholder sales cycles from discovery to close.

Required skills

• Solid understanding of cloud computing and the AWS ecosystem, including the differences between IaaS, PaaS and SaaS and cloud migration strategies.
• Nice to have: active AWS certifications (e.g. AWS Certified Cloud Practitioner, AWS Certified Solutions Architect - Associate), experience with an AWS partner or systems integrator, and familiarity with data lakes, pipelines and analytics.