Pre-Sales Engineer - AI Solutions

Job Title: Pre-Sales Engineer - AI Solutions

 

Location:

[Location] (Opportunities for remote/hybrid/flexible work available)

 

Reports to:

Head of Pre Sales, Head of Solutions Engineering, VP Sales

 

Role Purpose

Join our dedicated team at [Company Name] and make a real impact in the field of artificial intelligence. We’re seeking a Pre-Sales Engineer – AI Solutions who can engage with potential clients to understand their goals and develop tailored strategies that showcase the full potential of our AI offerings. This role combines technical consulting, customer relationship management, and a deep understanding of machine learning technologies to create compelling proposals and demonstrations. If you’re looking to collaborate on meaningful projects while enjoying the flexibility of remote or hybrid work, this could be the perfect opportunity.

 

Company Overview

[Company Name] is a forward-thinking organization focused on delivering advanced AI solutions to clients in [Industry] and beyond. Our team thrives on curiosity, collaboration, and integrity, aiming to provide innovative applications that address complex real-world challenges. Recognized for our inclusive culture and supportive environment, we prioritize professional growth and continuous learning. We invest in state-of-the-art research, champion new ideas, and celebrate the accomplishments of our teams. As part of our commitment to excellence, we offer robust training programs, clear development paths, and opportunities to work with emerging technologies in AI and machine learning.

 

Key Responsibilities

• Technical Consultation

  • Collaborate with prospective clients, sales teams, and solution architects to interpret requirements and shape AI-based solutions.

  • Deliver in-depth presentations, demonstrations, and workshops that emphasize how our products address specific challenges.

• Solution Design and Proposal Development

  • Translate business objectives into technical specifications by analyzing client data, workflows, and ecosystem constraints.

  • Prepare solution proposals, high-level architectures, and roadmaps, ensuring each aligns with measurable outcomes and ROI.

  • Respond to RFPs and RFIs with accurate, detailed technical information, including architecture diagrams and performance metrics

• Proof-of-Concept (PoC) Execution

  • Design and implement PoCs to highlight the value of AI models, including NLP, computer vision, or predictive analytics.

  • Work alongside cross-functional teams (data scientists, ML engineers, project managers) to meet deadlines and confirm solution feasibility.

• Client Engagement and Relationship Management

  • Act as a trusted advisor by proactively addressing client queries, guiding technical decisions, and recommending best practices.

  • Maintain open communication channels with customer stakeholders, gathering feedback and feeding it back to product teams.

• Cross-Team Collaboration

  • Coordinate with product management and engineering to relay client requirements that influence future product enhancements.

  • Partner with the sales organization to build strong customer relationships and support commercial goals throughout the sales cycle.

• Industry Awareness and Thought Leadership

  • Keep abreast of the latest AI frameworks, development tools, and market trends to position [Company Name] as a source of expertise.

  • Contribute to content creation, such as whitepapers, technical blogs, and conference talks, that highlight real-world AI success.

 

Required Skills and Qualifications

• Education and Foundation

  • Bachelor’s degree in Computer Science, Engineering, or a closely related field (or equivalent practical experience).

  • Solid grounding in AI technologies such as machine learning algorithms, neural networks, NLP models, or computer vision techniques.

• Technical Experience

  • Proficiency in at least one programming language (Python, Java, or C++), along with familiarity in AI frameworks (TensorFlow, PyTorch, or Keras).

  • Adept at cloud platforms (AWS, Azure, GCP) and understanding containerization/orchestration (Docker, Kubernetes) for AI workloads.

  • Experience with data processing, analytics platforms, and version control tools (Git, GitHub).

• Communication and Presentation

  • Ability to simplify complex concepts for non-technical audiences without losing essential technical depth.

  • Previous experience delivering high-impact product demos, presentations, or workshops in client-facing settings.

  • Skilled at building strong relationships with clients, teams, and stakeholders across various roles and responsibilities.

• Analytical and Problem-Solving Abilities

  • Attention to detail when debugging or optimizing PoC implementations.

  • Capacity to propose actionable solutions based on data interpretation and feasibility studies.

• Adaptability and Collaboration

  • Willingness to adjust to changing client needs, project timelines, or emerging AI technology trends.

  • Comfortable working in cross-functional environments, balancing multiple projects, and coordinating efforts among teams.

 

Preferred Experience and Attributes

• Enterprise and Consulting Background

  • Proven track record in handling high-value enterprise clients, large-scale data, or mission-critical AI deployments.

  • Consulting experience or a history of leading multiple client engagements in a pre-sales capacity.

• Leadership and Mentorship

  • Enthusiasm for sharing knowledge, mentoring junior engineers, and advocating best practices within the organization.

• Industry Recognition

  • Contributions to open-source AI projects, thought leadership in the form of conference talks, or published research.

​

Perks and Benefits:

Clearly outline the benefits and perks of the role.

 

How to Apply:

End with a strong call to action encouraging candidates to apply. Include a direct link to the application page and provide contact information for further queries.

​

Please ensure each job description includes all relevant information in compliance with local, state, and national laws. This includes:

 

• Salary Information: Provide a clear salary range to maintain transparency and meet legal requirements.

• Privacy Policies: Protect candidate privacy by following all applicable data protection and privacy laws.

• Equality & Non-Discrimination: Include an equal opportunity statement to uphold our commitment to a diverse, inclusive workplace that does not discriminate based on race, gender, age, disability, or any other protected characteristic.

• Accessibility: Make reasonable accommodations available for candidates with disabilities and include information on how they can request assistance throughout the hiring process.

• Environmental and Social Responsibility: If your company has sustainability initiatives or community engagement programs, mentioning them briefly can attract candidates who prioritize working for socially responsible employers.

• Transparent Hiring Process: Briefly explain the hiring process (e.g., “Our interview process typically includes three stages: an initial screening, a technical interview, and a final interview”) to help candidates know what to expect.