Job Description
Job Title: Senior AI Engineer
Location: Dallas, TX
Role Overview
- Lead the design, development, and deployment of advanced AI systems
- Build cutting-edge solutions across machine learning, NLP, generative AI, LLMs, and multi-agent orchestration
- Drive innovation across our product portfolio by solving real-world problems
Key Responsibilities
- Architect, build, and deploy production-grade AI/ML systems at scale
- Design and develop RAG pipelines, agentic AI systems, and multi-agent orchestration solutions
- Build intelligent automation flows and conversational AI agents using frameworks like LangGraph, LangChain, and Microsoft Copilot Studio
- Develop time-series forecasting and anomaly detection models for real-world business use cases
- Apply advanced prompt engineering and integrate Model Context Protocol (MCP) to connect AI agents with enterprise systems
- Own the full AI project lifecycle — from data ingestion and preprocessing through model training, evaluation, deployment, and monitoring
- Collaborate with data scientists, software engineers, and product managers to translate business needs into AI-powered solutions
- Optimize model performance and ensure robustness, fairness, and explainability
- Stay current with the latest AI/ML research and bring relevant advancements into our stack
Our Technology Landscape
- Retrieval-Augmented Generation (RAG) pipelines
- Agentic AI frameworks (e.g., LangGraph, LangChain)
- Multi-agent orchestration systems
- Model Context Protocol (MCP) integrations
- Advanced prompt engineering
- Time-series modeling, forecasting, and anomaly detection
- Intelligent automation flows and workflow orchestration
- Microsoft Copilot Studio for building and deploying custom copilots and conversational AI agents
Required Qualifications
- Bachelor's or Master's degree in Computer Science, AI, Machine Learning, or a related field (PhD preferred)
- 5\+ years of AI/ML engineering experience with a proven track record of shipping models to production
- Proficiency in Python and ML libraries such as TensorFlow, PyTorch, Scikit-learn, etc.
- Experience with cloud platforms (AWS, Azure) and MLOps tools
- Strong understanding of data structures, algorithms, and software engineering principles
- Solid grounding in software engineering best practices and system design
- Experience designing and building automation workflows or process automation systems
- Excellent problem-solving and communication skills
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