Job Title AI Engineer- CT (Connected Technologies)
Department 350-Connected
Location: Plano, Texas, United States
Role Overview
The AI Engineer will explore cutting-edge advancements in Generative AI and LLM ecosystems, design rapid prototypes, evaluate models/tools, and collaborate with engineering teams to turn experimental ideas into scalable production systems.
Key Responsibilities
1. AI Research & Emerging Tech Exploration
Continuously research new advancements in Generative AI, LLMs, agentic frameworks, and multimodal models.
Evaluate tools like ChatGPT, GitHub Copilot, LangChain, LangSmith, CrewAI, vector DBs, RAG frameworks, and orchestration platforms.
Identify opportunities to apply new AI capabilities to real business challenges.
2. Rapid Prototyping & Development
Build hands-on prototypes and POCs using Python and AI SDKs.
Develop and iterate on AI workflows, pipelines, agentic systems, and retrieval‑augmented applications.
Validate feasibility of concepts before engineering teams take them to production.
3. Experimentation & Model Evaluation
Conduct model benchmarking, prompt engineering, fine‑tuning, and performance evaluation.
Compare models and architectures; recommend the best-fit solutions.
Document experiments, logs, findings, and reproducible code samples.
4. Collaboration & Implementation
Work closely with engineering teams to convert prototypes into scalable production systems.
Translate research results into actionable architecture and deployment recommendations.
Align AI prototypes with business and product requirements.
5. Thought Leadership & Knowledge Sharing
Track industry trends, research papers, open-source innovations, and market developments.
Present demos, insights, and proposals to stakeholders.
Conduct internal workshops and contribute to technical knowledge sharing.
Requirements
Technical Skills
Bachelor’s in CS, AI, Data Science, or equivalent experience.
5+ years in AI engineering, ML research, or AI prototyping roles.
Strong Python programming and experience with TensorFlow/PyTorch.
Hands-on expertise with LLMs, prompt engineering, RAG frameworks, LangChain, LangSmith, vector DBs, and GenAI tools.
Experience building POCs and experimental AI applications.
Applied AI & Tool Knowledge
Understanding of AI platforms: OpenAI, Anthropic, Hugging Face, Azure AI, AWS Bedrock, etc.
Familiar with developer tools like GitHub Copilot and modern MLOps workflows.
Skilled in API integrations, tuning, evaluation, and model experimentation.
