Gen AI Engineer

Bachelor’s degree in Computer Science, Computer Engineering, Technology, Information Systems (CIS/MIS), Engineering or related technical discipline, or equivalent experience/training

2+ years of full Software Development Life Cycle (SDLC) experience designing, developing, and implementing large-scale applications in hosted production environments

3+ 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

5 years of full Software Development Life Cycle (SDLC) experience

Prior experience designing and building agentic systems

1+ yr 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.)