Quick Overview
Job Description
Position - Senior AI Engineer
Location: Fort Worth, TX 76155
Candidate must work onsite Tuesdays - Thursdays; Virtually Mondays/Fridays.
There will be 1 round In-person interviews at Fort Worth, TX
This role is for 5-7 years of experience.
Top 3 Must Haves:
· Gen AI Production Development
- Python Coding
- AI Engineering
Minimum Qualifications- Education & Prior Job Experience
· Bachelor's degree in Computer Science, Computer Engineering, Technology, Information Systems (CIS/MIS), Engineering or related technical discipline, or equivalent experience/training
- 5+ years of full Software Development Life Cycle (SDLC) experience designing, developing, and implementing large-scale applications in hosted production environments
- 5+ years of professional, design, and open-source experience
Preferred Qualifications- Education & Prior Job Experience
· Master's degree in Computer Science, Computer Engineering, Technology, Information Systems (CIS/MIS), Engineering or related technical discipline, or equivalent experience/training
- 7 years of full Software Development Life Cycle (SDLC) experience
- Prior experience designing and building agentic systems
- 2+ years prior experience developing and implementing AI solutions using Large-Language Models (LLMs)
- Airline or transport industry experience is a plus
Skills, Licenses & Certifications
· Practical understanding of transformer architectures and how modern LLMs work
- Experience building agentic orchestration using frameworks such as Semantic Kernel, LangChain/LangGraph, Microsoft Copilot Studio, OpenAI/Anthropic tool-calling patterns, or equivalent internal frameworks
- Proficiency in prompt engineering: systematic prompt design, few-shot learning, chain-of-thought, and prompt optimization for foundation models
- Knowledge of vector databases (e.g., Pinecone, FAISS, Weaviate, Chroma) and RAG architecture patterns
- Experience with LLM evaluation methods, including LLM-as-a-judge, automated benchmarking, and regression testing for model outputs
- Proficiency in post-deployment model maintenance, including observability, monitoring, cost optimization, and drift detection
- Experience developing and implementing governance frameworks and controls for responsible AI
- Familiarity with AI-assisted development tools (e.g., GitHub Copilot, Cursor, Claude Code) is a plus
- Knowledge of experimentation and measurement: A/B testing, KPI instrumentation, and operational analytics
- Strong proficiency in Python; working knowledge of Java or another enterprise language
- Proficiency in object-oriented design techniques and principles
- Experience with cloud platforms (Azure, AWS, or Google Cloud Platform) and cloud-native development patterns
- Experience with CI/CD pipelines and DevOps toolchain: Git, GitHub, Jenkins, ADO Pipelines, or equivalent
- Experience with RESTful API design and integration patterns (JSON, microservices)
- Experience in Agile methodologies, such as SCRUM
- Proficiency in Microsoft Office Tools (Project, Excel, Word, PowerPoint, etc.)
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