GenAI Lead

GlobalPoint; Charlotte (NC); Sur place; USD 180 000 - 250 000; Plein temps

Résumé du poste

GlobalPoint in Charlotte, NC is seeking a GenAI Lead to architect and deliver enterprise GenAI platforms. You will design agentic AI workflows, build RAG pipelines, and implement scalable API services using Python.

You will mentor engineers, drive MLOps practices, and collaborate with stakeholders to translate business needs into scalable AI solutions.

Qualifications

• Experience with Generative AI and large language models.
• Proven ability to design and deploy RAG pipelines and knowledge systems.
• Strong Python skills and API development experience.

Responsabilités

• Lead architecture and implementation of GenAI platforms and applications.
• Design agentic AI and multi-agent workflows with industry tools.
• Build scalable APIs/microservices using Python frameworks.
• Implement AI governance, security, and guardrails practices.
• Mentor teams and translate business needs into scalable AI solutions.

Connaissances

Generative AI

LLMs

Python

REST APIs

FastAPI

Flask

RAG pipelines

Vector databases

MLOps

Docker

Kubernetes

Formation

Bachelor's or Master's in CS/Engineering/AI

Outils

Pinecone

Weaviate

ChromaDB

FAISS

Elasticsearch/OpenSearch

OpenAI GPT/ Claude/ Gemini / Llama

Description du poste

Long term contract

10+ years of work experience with Application Development

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