Senior Manager Presales

Required Skills and Qualifications:

• Bachelors degree in Engineering, Computer Science, Business, or a related field.
• Proven experience (4+ years) in a pre-sales or solutions engineering role, preferably in AI, Data Collection, Data Annotation, or a similar field.
• Strong knowledge of AI data services, machine learning models, and AI/ML platforms.
• Familiarity with data annotation tools such as Labelbox, SuperAnnotate, AWS SageMaker Ground Truth, or similar tools.
• Experience with linguistics or multilingual data projects is a plus.
• Excellent communication, presentation, and interpersonal skills, with the ability to explain complex technical concepts to non-technical audiences.
• Ability to work in a fast-paced, dynamic environment and manage multiple projects simultaneously.
• Experience working with cross-functional teams including engineering, sales, and product management.
• Strong problem-solving skills and attention to detail.
• Must-Have Skills:

1. AI & Data Expertise:
• AI Training Data, Data Annotation
  Deep understanding of the AI/ML landscape, data collection, and data annotation workflows.
• Machine Learning Concepts
  Knowledge of supervised and unsupervised learning, NLP, computer vision, and model training processes.
2. Pre-Sales & Solutions Architecture:
• Technical Solution Design
  Ability to craft customized AI solutions based on client requirements, with clear technical proposals.
• RFP/RFI Management
  Experience in managing the entire proposal process, responding to RFPs, and creating accurate, compelling documentation.
3. Client Engagement & Communication:
• Client-Centric Approach
  Expertise in understanding client challenges, gathering requirements, and presenting the right AI data solutions.
• Technical Communication
  Ability to translate complex technical information into simple, value-driven messaging for both technical and non-technical audiences.
4. Cross-Functional Collaboration:
• Interdepartmental Collaboration
  Experience working with sales, engineering, product, and delivery teams to ensure a seamless customer experience and solution alignment.
5. Vendor & Partner Management:
• Vendor Sourcing and Onboarding
  Ability to identify, negotiate, and manage relationships with global vendors and freelancers for AI data projects.
• Contract & Budget Management
  Negotiation skills to source solutions within budget, along with managing vendor contracts and timelines.
6. Analytical Thinking & Problem Solving:
• Solution-Oriented Mindset
  Ability to troubleshoot client problems and devise innovative solutions that meet the projects technical and commercial goals.

Tools Knowledge:

1. Presentation Tools:
• Microsoft PowerPoint, Google Slides, Prezi
  Used for developing and delivering client presentations, product demos, and proposals.
2. Collaboration & Project Management Tools:
• Jira, Asana, Confluence, Slack
  These tools help manage internal team collaborations and ensure seamless pre-sales to post-sales handoffs.
3. Data Visualization Tools:
• Tableau, Power BI
  Familiarity with data visualization software to present insights to clients and stakeholders in a meaningful way.
4. CRM Tools:
• These tools help manage the sales pipeline, track customer interactions, and monitor pre-sales activities.
5. AI/ML Tools & Platforms:
• AWS SageMaker Ground Truth, Labelbox, SuperAnnotate
  These are essential for managing data annotation, training datasets, and scaling AI models.
• Google Cloud AI, Azure AI
  Familiarity with cloud-based AI platforms to help clients build, deploy, and manage machine learning models.
6. Data Annotation Tools:

SuperAnnotate, CVAT, Scale AI
Hands-on knowledge of these annotation platforms to design and propose data labeling solutions.