Artificial Intelligence Engineer

About the Opportunity

We are seeking a hands-on Artificial Intelligence Engineer with experience in backend development, AI integration, and search infrastructure to help build the technical foundation of an early-stage MVP. This role is ideal for someone who enjoys building from the ground up, integrating AI into real-world applications, and taking ownership of technical implementation. Students and aspiring engineers are welcome to apply if they possess the technical skills to build, problem-solve, and contribute.

Ideal Candidate

We are looking for a self-directed, technically capable engineer who can:

• Take ownership of backend implementation and technical decisions.
• Translate product requirements into working software.
• Explain technical recommendations clearly.
• Build and integrate APIs, databases, AI models, and search services.
• Recommend practical, cost-effective technologies for an early-stage product.

Key Responsibilities

Backend Development and Architecture

• Design and implement backend services and APIs.
• Connect AI models, search services, databases, and the frontend.
• Design database structures for companies, products, services, capabilities, certifications, and source information.
• Implement appropriate security, data validation, error handling, and access controls.

AI Integration and Search Infrastructure

• Integrate LLM APIs to interpret natural-language queries and identify user requirements.
• Build systems to retrieve, filter, rank, and organize relevant companies, AI tools, products, and services.
• Evaluate keyword search, semantic search, embeddings, and vector search.
• Develop relevance-based matching and filtering based on user-defined requirements.
• Build backend functionality for comparing multiple search results side by side.

Data Sources and Integrations

• Integrate external APIs, permitted web-search services, public datasets, and relevant specialized directories.
• Build processes to collect, normalize, structure, and update retrieved information.
• Help the platform discover relevant options across multiple sources.
• Preserve source links for user review.

MVP Development

• Recommend an appropriate backend architecture and technology stack.
• Develop, test, deploy, and document the backend.
• Collaborate on integration with the frontend.
• Build a practical foundation for future features and data sources.

Requirements & Tech Stack

Required Qualifications

• Experience with backend development and API design.
• Experience with coding such as Python and FastAPI, or an equivalent backend framework.
• Experience with relational databases such as PostgreSQL or comparable technologies.
• Experience integrating AI models or LLM APIs into applications.
• Experience working with external APIs and structured data.
• Understanding of search, information retrieval, filtering, or relevance ranking.
• Ability to independently develop, test, troubleshoot, and deploy software.

Preferred Qualifications

• Experience building AI-powered search, discovery, recommendation, or data-driven applications.
• Familiarity with semantic search, embeddings, retrieval-augmented generation (RAG), or vector databases.
• Experience with search technologies such as Elasticsearch, OpenSearch, or PostgreSQL full-text search.
• Familiarity with Claude or other AI-assisted development tools.
• Experience using VS Code or similar development environments.
• Experience with cloud hosting and deployment platforms, such as AWS, Vercel, or comparable services.
• Experience developing MVPs or working with early-stage startups.
• A portfolio, GitHub repository, or demonstration of previous work.