JOB DESCRIPTION

We are seeking a Pre-Sales Solution Architect (AI & Cloud) with expertise in AWS cloud platforms and AI/ML solutioning. This role blends technical expertise with business development, where you will work closely with sales teams, partners, and clients to design and deliver innovative AI-driven solutions on the cloud. The ideal candidate has pre-sales experience, solution architecture skills, and a proven track record delivering AI and cloud solutions for commercial and public sector customers

REQUIREMENTS:

• Bachelor’s degree or higher in Computer Science, Information Systems, or related field.
• Strong background in solution architecture, with hands-on experience in AWS cloud platforms
• Proven expertise in AI/ML solutioning, including model deployment, MLOps, and data engineering.
• Pre-sales experience in a vendor/SI environment, including client engagement, proposal development, and solution presentations.
• Solid understanding of cloud-native architectures
• Excellent communication skills with the ability to influence C-level stakeholders and simplify complex technical concepts.
• Professional certifications such as AWS Certified Solutions Architect – Professional, AWS Certified Machine Learning – Specialty, or similar highly desirable.

• Partner with business development and sales teams to engage clients, understand requirements, and shape solution strategies.
• Lead pre-sales activities including client workshops, technical presentations, solution demonstrations, RFP/RFI responses, and proposal development.
• Design end-to-end AI and cloud architectures on AWS, covering cloud infrastructure, data pipelines, AI/ML models, APIs, and enterprise integrations.
• Define architecture blueprints, best practices, and reference designs for secure, scalable, and resilient deployments.
• Act as a trusted technical advisor to clients, helping them identify opportunities for AI and cloud adoption that drive measurable business outcomes.
• Collaborate with delivery teams to ensure proposed solutions are practical, cost-effective, and successfully implemented.
• Provide technical leadership and mentorship to engineering, DevOps, and data science teams throughout project lifecycles.
• Stay updated on emerging AI/ML technologies, AWS services, and cloud-native trends to position the company as an innovation leader.