- Company Name
- Paradigm
- Job Title
- Applied AI Engineer
- Job Description
-
Job Title: Applied AI Engineer
Role Summary: Design, develop, and deploy production-ready AI systems that automate construction workflows using large language models, computer vision, and retrieval-augmented generation. Bridge the gap between ML models and enterprise platforms to deliver reliable features for design, estimating, and procurement.
Expactations:
- Deliver end‑to‑end AI solutions that scale in live construction environments.
- Collaborate cross‑functionally with data, product, and software engineering teams.
- Continuously evaluate and improve model accuracy, efficiency, and reliability.
Key Responsibilities:
- Build and maintain agentic AI pipelines combining LLMs, multimodal models, and rules‑based logic.
- Design RAG workflows to connect LLMs with real‑time project data, specs, and plan sets.
- Fine‑tune domain‑specific models for plan understanding, entity extraction, and BOM generation.
- Implement APIs, SDKs, and integration layers for AI outputs in ERP, design, and estimating tools.
- Optimize inference, monitor system health, and enforce security and compliance standards.
- Create data pipelines for training, validation, and continuous feedback, ensuring reproducibility and version control.
- Conduct model evaluation (zero/few‑shot tests, Chain‑of‑Thought analysis, LLM‑as‑a‑judge) and cost/performance optimization.
- Stay current with emerging AI frameworks, agentic orchestration, and developer tooling.
Required Skills:
- 5+ years of production AI/ML engineering experience, with recent work on LLMs or agentic architectures.
- Proficiency in Python, PyTorch or TensorFlow, and LLM integration (OpenAI, Anthropic, Hugging Face).
- Experience building RAG pipelines, vector databases, and semantic search.
- Familiarity with agentic orchestration (LangGraph, Temporal, n8n, etc.) and enterprise AI platforms (Azure AI, AWS Bedrock, Vertex AI).
- Strong prompt engineering, evaluation, and cost‑optimization skills.
- Knowledge of multimodal data (CAD/BIM, images, text) and data labeling/feedback loops.
- Excellent problem‑solving, curiosity, and collaborative mindset.
Required Education & Certifications:
- Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or related field.
- Certifications in cloud AI platforms (Azure AI, AWS Bedrock, Vertex AI) are a plus.