AI Backend Engineer

Seez•Fort Lauderdale, FL

2d•Remote

About The Position

Seez is an AI-powered automotive technology company transforming how vehicles are bought and sold. Since 2016, they’ve been building scalable SaaS and digital retail solutions that help dealerships, OEMs, and marketplaces deliver smarter, more seamless car buying experiences. They are looking for an engineer who combines strong backend engineering fundamentals with modern machine learning expertise. This role sits at the intersection of software engineering and AI, helping to build intelligent, production-ready applications that power the next generation of automotive retail. The ideal candidate enjoys building scalable software, experimenting with the latest AI technologies, and solving real customer problems. Passion, ownership, and strong technical judgment are essential for success in this role.

Requirements

4+ years of experience in software engineering.
Strong commercial experience building backend applications with Python and Node.
Experience developing and deploying machine learning or LLM-powered applications.
Experience building REST APIs, GraphQL, and backend services.
Experience with FastAPI or similar Python web frameworks.
Experience working with SQL databases such as PostgreSQL.
Familiarity with Docker and cloud platforms (AWS preferred).
Experience using Git and modern software development practices.
Strong problem-solving skills with a pragmatic approach to shipping software.
Strong written and verbal English communication skills.

Nice To Haves

Experience with LangChain or similar AI orchestration frameworks.
Experience with vector databases such as Pinecone, pgvector, Weaviate or Qdrant.
Experience building Retrieval-Augmented Generation (RAG) applications.
Knowledge of prompt engineering and LLM evaluation techniques.
Experience deploying AI applications into production environments.
Familiarity with CI/CD pipelines and infrastructure as code.

Responsibilities

Design, build and maintain scalable backend services using Python, Node and .NET.
Develop production-ready AI applications powered by Large Language Models (LLMs).
Build and optimise Retrieval-Augmented Generation (RAG) pipelines and vector search solutions.
Integrate foundation models such as OpenAI, Anthropic and Gemini into customer-facing products.
Design, build and maintain REST APIs that power AI services.
Work with structured and unstructured data to improve AI performance and user experience.
Optimise applications for performance, scalability and reliability.
Write clean, maintainable and well-tested code.
Collaborate closely with Product, Design and Engineering to deliver features from concept through production.
Monitor, evaluate and continuously improve AI system performance.