Pre-Sales Engineer

Job Title

Pre-Sales Engineer

Job Scope

The Lead Consultant - Pre-Sales is responsible for strategizing and coordinating with the sales team and other departments on all technical and business-critical issues. S/He serves as the technical and strategic authority, building strong relationships with vendors, partners and customers while driving the business through multiple initiatives and overseeing the Pre-Sales Consulting team

Main Duties and Responsibilities

• Oversee and mentor the Pre-Sales Consulting team, ensuring quality and consistency in pre-sales support across the organization.
• Act as the go-to subject matter expert in technical/solution design for the assigned products/services portfolio.
• Develop and implement specific accounts, product(s), service(s) and sales strategies for the team.
• Lead in the qualification of opportunities, providing higher-level strategy and technical guidance throughout the sales lifecycle.
• Manage, coordinate and provide oversight for proof of concepts (POC), request for proposals (RFP) and the technical aspects of deal closures.
• Facilitate and lead technical sales calls and customer meetings at an executive level.
• Evaluate the IT landscape, ensuring that the solutions provided are aligned with the industry’s best practices and client needs.
• Work with Sales, Services and other departments to align solutions with the overall business strategy.
• Lead the sales bid process, including the preparation and review of RFIs, RFPs and RFQs.
• Drive vendor relations and negotiate to procure the best solutions, balancing cost and quality.
• Prepare and manage team performance metrics and KPIs.
• Stay updated on market trends, products and competitor landscapes and disseminate this knowledge to the team.
• Implement and enforce the use of systems like CRM for efficient opportunity and deal management.

Position Requirements

• Proven leadership and management skills to guide cross-functional teams in AI, GPU computing, and smart manufacturing solution design.
• Deep understanding of GPU-accelerated computing architectures (NVIDIA A100, H100 GPUs), CUDA programming fundamentals, and NVIDIA AI Enterprise software stack (TensorRT, DeepStream, CUDA).
• Technical expertise in Deep Neural Network design and deployment, including model selection, training, optimization, and operationalization in production environments.
• Solid experience with Smart Manufacturing technologies, including Industrial IoT (IIoT), edge computing, AI-driven automation, and real-time data analytics.
• Proficiency with major AI/ML frameworks (PyTorch, TensorFlow, Keras) and their integration into enterprise workflows.
• Knowledge of hybrid and multi-cloud AI architectures (Azure, AWS, GCP), including workload orchestration, data pipelines, and MLOps.
• Vendor certifications in NVIDIA Deep Learning Institute courses, Azure AI, or equivalent.
• Ability to develop and deliver persuasive demos, proofs of concept, and technical presentations for enterprise and public sector clients.
• Skilled in quantifying ROI, TCO, and business impact of AI and smart manufacturing solutions.
• Proficient in CRM tools, MS Office, and AI lifecycle management platforms.
• Strong understanding of data governance, security best practices, and compliance frameworks related to AI deployments.

Education

Bachelor’s degree in Computer Engineering, Computer Science or any other related field.

Experience

At least 3 years of relevant experience.

#LI-AA3