Senior AI Application Developer

Job-:
Information Technology

Location:

Orlando, FL, United States Workplace:
Hybrid

Schedule:

Full time Posted:
At Signature Aviation we are modernizing operations and customer experience through advanced data platforms and artificial intelligence. We are hiring an Senior AI Application Developer to build the AI capabilities the business actually uses — agentic systems, LLM-powered applications, and intelligent automation on Azure — together with the retrieval, feature, and data pipelines those capabilities depend on. You own the capability end to end: the agent or assistant, the data it reasons over, the pipelines that feed it, and the evaluation that proves it works.

You will not hand off at the data boundary, and you will not be handed a clean dataset.

Working model — forward deployed: you embed with the business unit and the engineering teams that own a use case, build inside their environment and release process, hand back a running system, and contribute what you learned to the shared accelerator library between deployments. Qualifications

Minimum Education and/or Experience5+ years in software, data, or ML engineering, with recent hands-on delivery.

You have built and deployed production-grade LLM applications or agent-based AI systems, and can explain how one worked, what broke, and how you knew it was good enough to ship.

Azure is required: hands-on Microsoft Foundry including Azure OpenAI models — deployments, the Foundry Models catalog, and Azure AI Content Safety.

Cloud-native application patterns on Azure: containers on Azure Container Apps or AKS, Azure Functions, CI/CD through Azure Dev Ops or Git Hub Actions, Microsoft Entra  identity, and Key Vault-backed configuration.

LLM application patterns — prompt design, RAG, function and tool calling, structured outputs, streaming — plus at least one orchestration framework: the Microsoft Agent Framework, the Foundry Agent Service, Semantic Kernel, Lang Chain/Lang Graph, or Llama Index.

Demonstrated data engineering: you have built or substantially rebuilt ingestion, transformation, embedding, or feature pipelines and kept them correct in production.

Vector or hybrid search in Azure AI Search, Cosmos DB, or pgvector;
Pinecone, Weaviate, or Redis Vector considered as equivalent depth.

You have evaluated model or prompt quality systematically. A lightweight harness you built yourself counts; anecdotal assessment does not.

Strong Python and working Type Script.

Experience integrating AI systems with enterprise data and operational platforms.

You have worked directly with the people who use what you build: embedded delivery, solutions engineering, or stakeholder-facing product work.

Sound instincts on secrets, access control, and PII, and the judgment to stop and ask.

Bachelor's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.

Preferred Qualifications Strong Lang Graph and multi-agent orchestration experience. MCP and enterprise tool integration. Microsoft Foundry, Azure OpenAI, Azure AI Search, Azure Databricks or Microsoft Fabric. OpenAI, Claude, Gemini, Llama or other foundation models. Langfuse, Lang Smith, Ragas, Promptfoo or Azure AI Evaluation SDK. MLflow and model lifecycle experience.

Experience with coding agents such as Claude Code, OpenAI Codex or Git Hub Copilot.

Experience working in a Forward Deployed Engineer, solutions engineering, consulting, startup or internal innovation role.

Aviation, logistics, mobility or other large-scale operational environments.

Additional Information This is an applied engineering role, not a research role: building statistical and forecasting models sits with data science, and you build the systems that put their outputs to work.

Responsibilities

E…