Senior Customer Solutions Engineer
Cloudflare
DNSFirewallsTCP/IP
Presales Solution Architect
Defined.ai
full-time
Posted on:
Location Type: Hybrid
Location: Lisbon • 🇵🇹 Portugal
Visit company websiteJob Level
Mid-LevelSenior
About the role
- 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.
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
data collectiondata annotationdata evaluationsolution architecturecost analysisworkflow designproject managementpricing modelsAI solutionsscalable project solutions
Soft skills
communication skillscollaborationtrust buildingproblem solvingclient engagementadaptabilityattention to detailcreativityorganizational skillsteamwork