AI Engineer (LLM & Agentic AI)

This position is for an Applied AI Engineer at Aiden Risk, focused on building and deploying production-ready AI systems. The ideal candidate will have the ability to transform large language model (LLM) capabilities into reliable and scalable applications. These applications may include intelligent agents, retrieval systems, browser automation, and data extraction tools. This role requires hands-on experience with real-world AI deployments rather than just theoretical knowledge or demos.

Key Responsibilities

- Design, build, and optimize Retrieval-Augmented Generation (RAG) pipelines and vector search systems tailored for real-world document datasets.
- Develop AI agents capable of tool calling, integrating with external APIs, and automating workflows.
- Implement browser automation and web data extraction using Playwright.
- Integrate LLMs from providers such as OpenAI, Anthropic, Gemini, and open-source models into production-grade applications.
- Create evaluation frameworks to assess AI system accuracy, reliability, latency, and cost-effectiveness.
- Build, test, and deploy Python-based AI services using Docker containers and cloud platforms.
- Continuously improve system performance, troubleshoot issues, and ensure reliability under real-world workloads.

Required Qualifications

- 1 to 2 years of professional software engineering experience with strong proficiency in Python programming.
- Practical experience developing applications using LLMs or generative AI models.
- Solid understanding of RAG, embeddings, vector search techniques, and familiarity with vector databases such as pgvector, Pinecone, or Chroma.
- Experience working with AI frameworks like LangChain or similar tools.
- Basic knowledge of APIs, Docker, and cloud platforms such as AWS or Google Cloud Platform (GCP).
- Strong problem-solving abilities and an engineering mindset focused on building, testing, and deploying functional solutions.

Preferred Qualifications and Benefits

- Experience with browser automation tools, particularly Playwright, is a plus.
- A demonstrated track record of building practical AI applications that go beyond tutorials or demos and operate reliably in production environments is highly valued.

This role offers the opportunity to work at the forefront of applied AI, contributing to innovative solutions that leverage cutting-edge LLM technologies in scalable, production-ready systems.