SeniorLead AI Engineer

Orlando, FL - USA

Monthly Salary: Not Disclosed

Posted on: 19 hours ago

Vacancies: 1 Vacancy

Job Summary

Job Description:

Evaluate AI Solutions: Analyze and benchmark AI platforms LLMs and agent frameworks for enterprise use.
Build Agentic Models: Design and develop AI agents capable of reasoning planning and executing multi-step tasks.
Engineer LLM Applications: Develop fine-tuned and optimized large language model applications with retrieval-augmented generation (RAG) pipelines.
Integrate with Enterprise Platforms: Embed AI capabilities into OMS CRM loyalty and digital platforms ensuring seamless user and operational experiences.
Establish AI Engineering Practices: Define standards for AI model deployment observability safety and compliance.
Collaborate Across Teams: Partner with Product Digital Engineering and Data Science to co-create AI-powered features and workflows.
Governance & Security: Implement guardrails privacy protections and compliance controls for AI-enabled applications.
Lead & Mentor: Guide a team of AI engineers and contribute to the enterprise AI strategy while remaining hands-on in technical delivery.

Responsibilities
Minimum Education and/or Experience:

Bachelors degree in Computer Science Engineering or related field; Masters or PhD preferred.
8 years of professional experience in software engineering AI/ML or data platforms.

Additional knowledge and skills:

Proven expertise in building and deploying LLM-powered applications and agentic AI models.
Hands-on experience with RAG pipelines embeddings and vector search in production.
Strong understanding of cloud-native AI services (Azure preferred).
Experience guiding teams delivering complex AI projects and driving innovation.
Experience with multimodal AI (vision speech structured data).
Background in AI governance responsible AI or applied ethics.
Publications patents or open-source contributions in AI/ML.
Familiarity with aviation logistics or operational technology domains.
Background in regulated industries (aviation logistics finance or hospitality).

Tech Stack & Skill Requirements:

AI/ML Frameworks: LangChain LlamaIndex Semantic Kernel Hugging Face.
LLMs: OpenAI GPT Anthropic Claude LLaMA Falcon or similar.
Vector Databases: Pinecone Weaviate Redis Vector or Azure Cognitive Search.
Programming Languages: Python (preferred) TypeScript/ for integrations.
Cloud Platforms: Azure AI/ML services Azure OpenAI AWS Bedrock or GCP Vertex AI.
MLOps: MLflow Azure Machine Learning or equivalent model lifecycle tools.
Observability: Langfuse Weights & Biases Application Insights for model monitoring.
Security: OAuth 2.0 RBAC data privacy compliance frameworks (GDPR PCI).

Job Description: Evaluate AI Solutions: Analyze and benchmark AI platforms LLMs and agent frameworks for enterprise use. Build Agentic Models: Design and develop AI agents capable of reasoning planning and executing multi-step tasks. Engineer LLM Applications: Develop fine-tuned and optimized la...

Job Description:

Evaluate AI Solutions: Analyze and benchmark AI platforms LLMs and agent frameworks for enterprise use.
Build Agentic Models: Design and develop AI agents capable of reasoning planning and executing multi-step tasks.
Engineer LLM Applications: Develop fine-tuned and optimized large language model applications with retrieval-augmented generation (RAG) pipelines.
Integrate with Enterprise Platforms: Embed AI capabilities into OMS CRM loyalty and digital platforms ensuring seamless user and operational experiences.
Establish AI Engineering Practices: Define standards for AI model deployment observability safety and compliance.
Collaborate Across Teams: Partner with Product Digital Engineering and Data Science to co-create AI-powered features and workflows.
Governance & Security: Implement guardrails privacy protections and compliance controls for AI-enabled applications.
Lead & Mentor: Guide a team of AI engineers and contribute to the enterprise AI strategy while remaining hands-on in technical delivery.

Responsibilities
Minimum Education and/or Experience:

Bachelors degree in Computer Science Engineering or related field; Masters or PhD preferred.
8 years of professional experience in software engineering AI/ML or data platforms.

Additional knowledge and skills:

Proven expertise in building and deploying LLM-powered applications and agentic AI models.
Hands-on experience with RAG pipelines embeddings and vector search in production.
Strong understanding of cloud-native AI services (Azure preferred).
Experience guiding teams delivering complex AI projects and driving innovation.
Experience with multimodal AI (vision speech structured data).
Background in AI governance responsible AI or applied ethics.
Publications patents or open-source contributions in AI/ML.
Familiarity with aviation logistics or operational technology domains.
Background in regulated industries (aviation logistics finance or hospitality).

Tech Stack & Skill Requirements:

AI/ML Frameworks: LangChain LlamaIndex Semantic Kernel Hugging Face.
LLMs: OpenAI GPT Anthropic Claude LLaMA Falcon or similar.
Vector Databases: Pinecone Weaviate Redis Vector or Azure Cognitive Search.
Programming Languages: Python (preferred) TypeScript/ for integrations.
Cloud Platforms: Azure AI/ML services Azure OpenAI AWS Bedrock or GCP Vertex AI.
MLOps: MLflow Azure Machine Learning or equivalent model lifecycle tools.
Observability: Langfuse Weights & Biases Application Insights for model monitoring.
Security: OAuth 2.0 RBAC data privacy compliance frameworks (GDPR PCI).