Hybrid Presales Solution Architect

at Defined.ai

• Job title: Presales Solution Architect
• Job type: Full Time
• Experience level: Mid level, Senior
• Salary: Not specified
• Degree requirement: Bachelor's Degree
• Location requirements: Hybrid, Lisbon, Portugal

About the role

• Pre-Sales Solution Architect supporting AI data projects and facilitating solutions. Join Defined.ai's mission in delivering high-quality data for artificial intelligence applications.

Responsibilities

• Support pre-sales effort for data collection, annotation and evaluation projects, as well as end-to-end solutions.
• Collaborate with clients to identify business challenges and provide appropriate solutions.
• Translate client use cases into data requirements and AI solutions.
• Skilled at communicating technical and operational aspects of a solution to clients, internal teams, and external vendors in clear, concise language.
• Setting up costing / pricing for the proposed solutions.
• Support the sales team in closing deals by gaining the clients trust with your deep knowledge and clear solutions.
• Be the creator and owner of the Solution Architecture document and related artifacts.
• Suggest improvements to the Defined.ai product lines based on your insights, client requests and feedback.
• Develop and present pricing models using Excel for various service offerings.
• Conduct cost analysis reviews, taking into account staff capacity, project management plans, timelines, and gross margin targets.
• Document workflows and build reusable solution templates for scaling or handing off to operations teams.

Requirements

• Minimum 3 years of experience in relevant roles.
• Higher education in a relevant field.
• Excellent written and verbal communication skills (fluency in English is a must).
• Proficiency in Microsoft Excel.
• Ability to estimate contributor hours, pricing, time on task, and gross margins based on project scope and constraints.
• Ability to design custom workflows using a crowd or human/service based solution (automated and manual).
• Ability to translate client requirements into technical workflows; skilled in creating scalable, cost-effective project solutions tailored to use case needs.
• Ability to collaborate with project managers, linguists, engineers, and QA leads to ensure solutions are technically sound and logistically feasible.
• Ability to work in a collaborative environment in different time zones and out of working hours when needed.
• Preferred but not required: Expertise in the full lifecycle of data for training AI models such as sourcing, ingestion, annotation, QA, and delivery.
• Preferred but not required: Experience working with and understanding the basic needs of tasks such as data collection for training AI models, transcription, entity recognition, classification, or fine tuning LLMs using a crowd solution.

Benefits

• Flexible working schedule and hybrid model.
• Excellent career development opportunities in a high growth company.
• Culture of feedback and continuous improvement.
• An international and diverse team.
• Continuous training opportunities.
• Fun activities.