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Senior/Lead AI Engineer

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Description

Senior/Lead AI Engineer
Position Responsibilities Note: Need Local Candidates
Title: Senior AI Engineer
Location: Orlando, FL (hybrid)

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:
  • Bachelor’s degree in Computer Science, Engineering, or related field; Master’s 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/Node.js 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).

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