Lead Search Engineer / Search Platform Architect

Job Description

eCommerce is a key digital enabler to Caterpillar s aftermarket parts and services growth strategy. Delivering on the Caterpillar brand promise of premium, high-quality solutions is an important element in accelerating the development and deployment of Caterpillar s expanded capabilities in eCommerce.

Position s Contributions to Work Group:

• The Lead Software engineer Ecommerce Search is responsible for setting the technical direction and overseeing the execution of advanced search solutions.
• This role combines strategic vision, hands-on technical expertise, and leadership to build scalable, high-performance search platforms that deliver exceptional user experiences.

Education & Experience Required:

• Bachelor s or master s degree in computer science or related field.
• 10+ years experience in total but with 7+ years of experience in search engineering.
• Also required are 3+ years in a technical leadership role.

Required Technical Skills

(Required)

• Strong understanding of modern search technologies and frameworks.
• Working experience with heavy equipment engineering or data analysis.
• Working experience with building Low-latency API in AWS using Memory-storage solutions.
• Familiarity with A/B testing frameworks for evaluating and improving
• Strong knowledge with cloud technologies (AWS, Azure, Google Cloud, etc.)
• Advanced experience with version control / repositories such as GitHub
• Experience operating in an Agile / Global team environment
• Must demonstrate strong initiative, interpersonal skills, and the ability to communicate effectively.

Typical task breakdown:

• Technical Strategy: Define and implement a long-term technical vision for the search platform to ensure scalability and adaptability to growing data volumes and query complexity.
• Team Leadership: Mentor and guide a team of search engineers through technical reviews, best practices, and collaborative problem-solving.
• Feature Development: Introduce advanced capabilities such as NLP, vector search, and personalization to enhance relevance and accuracy.
• Data Analysis & Optimization: Build search capabilities with measurable KPIs (e.g., CTR, Query Distribution, Zero Search) and leverage analytics to continuously improve search performance.
• Cross-Functional Collaboration: Partner with product managers, data scientists, and engineering teams to align search initiatives with business objectives