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GenAI Lead

$60–$65 an hour

GlobalPoint · Charlotte, NC · Hybrid · Full-time

Build · Found · posted today

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Experience asked for: at least 10 years

Read out of the requirements below, in the employer's own words — not from a dropdown. Where a posting lists several requirements we take the largest, because a requirements list is a list of things you need all of.

GenAI Lead Charlotte, NC Long term contract 10+ years of work experience with Application Development 4+ years of work experience with Generative AI Development 6+ years of work experience with Python (Programming Language) Key Responsibilities • Lead the architecture, design, and implementation of enterprise GenAI platforms and applications. • Design Agentic AI and multi-agent workflows using LangChain, LangGraph, CrewAI, AutoGen, Semantic Kernel, or Llama Index. • Build and optimize RAG pipelines, vector search solutions, embedding workflows, and enterprise knowledge systems. • Develop AI solutions for business process automation, knowledge management, intelligent document processing, conversational AI, decision support, and developer productivity. • Build scalable APIs and microservices using Python, FastAPI, or Flask. • Implement AI monitoring, observability, security, governance, guardrails, and responsible AI practices. • Optimize prompts, context management, model performance, latency, reliability, and cost. • Drive cloud deployment, CI/CD, DevOps, and MLOps practices. • Collaborate with stakeholders to identify AI opportunities and translate business needs into scalable solutions. • Mentor engineering teams and establish enterprise AI best practices. Required Qualifications • Bachelor s or Master s degree in Computer Science, Engineering, Artificial Intelligence, or a related field, or equivalent practical experience. • Strong expertise in Generative AI and LLMs, including OpenAI GPT, Claude, Gemini, Llama, or Mistral, with knowledge of prompt engineering, fine-tuning, function calling, tool integration, agent orchestration, context management, and memory handling. • Proficiency in Python and experience building REST APIs, microservices, and enterprise integrations using FastAPI or Flask. • Practical experience with RAG architecture, vector databases, embedding models, semantic and hybrid search, and document ingestion pipelines, using technologies such as Pinecone, Weaviate, ChromaDB, FAISS, Milvus, Elasticsearch, or OpenSearch. • Knowledge of Docker, Kubernetes, CI/CD, GitHub Actions, Jenkins, GitLab CI, Terraform, and cloud platforms such as AWS, Azure, or GCP. Familiarity with MLOps, model deployment, monitoring, logging, AI governance, security, SQL/NoSQL databases, and data pipelines. Strong communication, problem-solving, and stakeholder management skills. Desired Qualifications • Working knowledge of Angular, TypeScript, or React. • Experience building AI copilots, enterprise assistants, conversational interfaces, or AI-powered user experiences. • Familiarity with MCP (Model Context Protocol). • Experience with Apache Airflow, n8n, Temporal, or Camunda. • Knowledge of AI security, responsible AI, governance, and model evaluation frameworks. • Ability to balance innovation with scalability, reliability, security, and operational excellence. Nice-to-Have • Experience in Capital Markets, Banking, Healthcare, Retail, Insurance, or other enterprise domains. • Familiarity with OCR, intelligent document processing, speech-to-text, text-to-speech, or multimodal AI. • Experience with AI observability, guardrails, red-teaming, and model risk management. • Contributions to AI communities, open-source projects, or technical innovation initiative

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