Artificial Intelligence Engineer

Position Overview

We’re seeking a multi-disciplinary AI Engineer to design, implement, and deploy LLM-driven agents with robust backend and front-end integration. In this role you will lead efforts in LLM agent design, prompting, fine-tuning, and MLOps while developing production-grade applications using modern web technologies. This full-time position is for local candidates in the Pittsburgh area (Hybrid remote in Pittsburgh, PA 15206).

Key Responsibilities

• LLM Agents & Prompt Engineering:
  • Architect and implement LLM agents using frameworks like LangGraph, PydanticAI, and Google ADK.
  • Build composable, tool-augmented reasoning chains (e.g., RAG, CoT, ReAct, planner-executor).
  • Integrate vector databases (e.g., FAISS, Pinecone, pgvector) and knowledge graphs (Neo4j) for retrieval-augmented generation and long-term chatbot memory.
  • Design and maintain robust prompt strategies.
• Evaluation, Testing & Observability:
  • Develop unit and behavioral tests for agents, tools, and workflows.
  • Create tooling for trace analysis, agent state debugging, and hallucination tracking.
  • Benchmark agent orchestration frameworks for performance and reliability.
• Model Fine-Tuning & MLOps:
  • Fine-tune models using LoRA, QLoRA, or full fine-tuning pipelines.
  • Integrate, deploy, and monitor models in production using cloud providers.
  • Establish logging, observability dashboards, and recovery workflows.
• FastAPI Development:
  • Develop and maintain scalable APIs with FastAPI supporting synchronous and asynchronous execution.
  • Implement state tracking, context-aware input dispatch, and modular plugin integration.

Required Qualifications

• 3+ years of Python experience in ML/AI systems using PyTorch or Tensorflow.
• 1+ years of experience in LLM agent development and prompt engineering with frameworks like LangGraph, PydanticAI, and Google ADK.
• Proven experience in fine-tuning LLMs.
• Familiarity with vector stores such as ChromaDB, Weaviate, or pgvector.
• Production experience with FastAPI, Docker, and MLOps.
• Expertise in Agentic Coding IDEs (Windsurf, Cursor or Claude Code).
• Bachelor’s or Master's degree in Computer Science.
• Familiarity with front-end frameworks and the ability to integrate front-end and back-end AI tools, including building basic dashboards or agent interfaces.

Preferred Qualifications

• Open-source contributions to LLM/agent tooling.
• Knowledge of asynchronous programming, websockets, and streaming APIs.

Benefits & Perks

• 401(k)
• Dental insurance
• Health insurance
• Paid time off
• Vision insurance
• Compensation: $90,000.00 - $120,000.00 per year