Generative AI Developers Who Build Beyond the Demo
Most organizations can get a generative AI prototype working quickly. Getting that prototype into production — handling real data, real users, real failure modes, and real compliance requirements — is a different challenge entirely. Scadea places GenAI developers who have made that journey, not just started it.
Generative AI Engineering Skills
- LLM integration: OpenAI GPT-4o, Anthropic Claude, Google Gemini, Meta Llama, Mistral
- Retrieval-Augmented Generation (RAG) architecture and vector database management
- LangChain, LlamaIndex, and custom orchestration frameworks
- Fine-tuning and instruction tuning on domain-specific corpora
- AI agent design: tool use, memory management, and multi-agent orchestration
- Guardrails, content filtering, and responsible AI implementation
- Prompt engineering, evaluation frameworks, and output quality measurement
Enterprise GenAI, Not Just Experiments
Our GenAI developers have shipped internal knowledge assistants, document processing pipelines, code generation tools, and customer-facing AI features in production. They understand operational concerns — latency, cost per token, hallucination mitigation, and data privacy — that separate a working product from a working demo.
Fast to Ship, Rigorous to Operate
Scadea GenAI candidates combine speed with rigor. They ship AI features quickly while building the evaluation and monitoring infrastructure that catches problems before users do.
Contact Scadea to hire a generative AI developer. Tell us what you are building and we will match you with someone who has already built something similar.