AI Specialist - #2910
Domain
Tech Stack
Must-Have Requirements
- ✓Master's degree in AI, Civil Engineering, or Computer Science OR equivalent practical experience
- ✓3+ years relevant experience
- ✓Strong Python proficiency
- ✓Experience building and deploying AI-powered applications
- ✓Hands-on experience with LLMs/GenAI systems
- ✓Backend/API development experience (FastAPI, Flask, or similar)
- ✓Solid understanding of machine learning fundamentals
- ✓Working knowledge of computer vision concepts
- ✓Cloud platform experience (Azure, AWS, or GCP)
- ✓Docker and production environment familiarity
Nice to Have
- -RAG frameworks experience (LangChain, LangGraph, LlamaIndex)
- -Vector databases and embeddings
- -ML/CV workflows exposure (OpenCV, PyTorch, TensorFlow)
- -Basic frontend experience (React)
- -Internal tools or platforms building experience
- -Document or visual data experience (PDFs, images)
Description
What we offer
Our excellent salary and benefits package includes medical, dental, vision, life insurance, short and long-term disability coverage, education reimbursement, 401(k), performance bonuses, and an employee stock program. Employee Resource Groups and Programs offered include the Young Professionals Group, Women at Wade Trim, Diversity, Equity and Inclusion, Professional Development, Leadership Development, Rotation Program, Mentor Program, Sustainability Program, and Wellness Program.
Position Description
We are looking for an AI Engineer to join our Information Technology Team in our Fort Worth or Pittsburgh office. Candidates must have a Masters in AI in Civil Engineering or in Computer Science with 0-2 years of relevant experience. Candidates must be proficient in Python, R, or similar programming languages. Candidates must have hands-on experience with machine learning algorithms, deep learning techniques, and AI systems. Candidates must also be self-motivated, work well with others, and have excellent writing, organizational, and communication skills. A flexible hybrid-remote work schedule is available after 30 days of employment.
Typical responsibilities include
AI Product & System Development (Primary Focus) Design, build, and maintain end-to-end AI-powered applications Apply GenAI, LLMs, and RAG pipelines to real-world engineering problems Integrate AI models into internal tools, platforms, and workflows Build and maintain backend services and APIs supporting AI functionality Ensure AI systems are reliable, performant, and usable in production ML / CV Collaboration & Application (Secondary Focus) Work with ML and CV models developed internally or externally Understand model inputs, outputs, limitations, and failure modes Assist with light model tuning, evaluation, or data preparation when needed Collaborate closely with research-focused AI engineers on model integration Deployment & Operations Deploy AI systems to cloud environments (Azure preferred) Monitor system performance, latency, and errors Iterate solutions based on user feedback and real usage Collaboration & Communication Work cross-functionally with AI researchers, full-stack engineers, and domain experts Communicate technical concepts clearly to non-AI stakeholders Document system designs, workflows, and operational guidelines Maintain a safe working environment
Education
Bachelor’s or Master’s degree in Computer Science, Engineering, or related field (Equivalent practical experience considered)
Skills/Experience
3+ years of experience. Core Skills Strong proficiency in Python Experience building and deploying AI-powered applications Hands-on experience with LLMs / GenAI systems Backend/API development experience (Fast API, Flask, or similar) Solid understanding of machine learning fundamentals Working knowledge of computer vision concepts (not research-level) Cloud & Systems Experience with cloud platforms (Azure, AWS, or GCP) Familiarity with Docker and production environments Experience working with document-based or visual data (PDFs, images) is a plus
Preferred qualifications
Experience with RAG frameworks (LangChain, LangGraph, LlamaIndex) Vector databases and embeddings Exposure to ML/CV workflows (OpenCV, PyTorch, TensorFlow) Basic frontend experience (React or similar) Experience building internal tools or platforms