Location: Charlotte, NC
Salary: $69.00 USD Hourly - $74.00 USD Hourly
Description: Senior AI Developer, Generative AI (Full Stack)We are not accepting C2C or 1099 arrangements.Location: Charlotte, NC (Hybrid: 3 days onsite, 2 days remote)
Schedule: Monday-Friday, 8:00 AM - 5:00 PM
Top RequirementsAbout the RoleWe are seeking a Senior AI Developer to architect, build, and deploy enterprise-scale Generative AI solutions. This role will focus on designing agentic workflows, Retrieval-Augmented Generation (RAG) platforms, and AI-powered applications using LangChain, LangGraph, and Google Vertex AI.
The ideal candidate combines strong software engineering fundamentals with deep expertise in GenAI technologies and cloud-native application development. You will partner with product managers, data scientists, platform engineers, and security teams to deliver scalable, secure, and production-ready AI solutions that drive measurable business value.
ResponsibilitiesDesign and Develop AI Solutions- Design and implement end-to-end Generative AI applications using Python, LangChain, and LangGraph.
- Build agentic workflows, state-based orchestration systems, and tool integrations that support complex business use cases.
- Develop scalable RAG solutions, including ingestion pipelines, embedding generation, vector indexing, and retrieval optimization.
- Create reusable AI frameworks, components, and services to accelerate development across teams.
Build Cloud-Native AI Platforms- Deploy and manage AI services using Google Cloud Platform (Google Cloud Platform) and Vertex AI.
- Develop RESTful APIs and backend services using FastAPI and microservices architecture.
- Containerize applications using Docker and deploy to Kubernetes/GKE environments.
- Implement CI/CD pipelines to support automated testing, deployment, and monitoring.
Improve AI Quality, Performance, and Reliability- Evaluate model performance using industry-standard metrics and GenAI evaluation frameworks.
- Optimize model responses, retrieval effectiveness, latency, and operational costs.
- Implement monitoring, tracing, logging, and observability solutions to ensure production reliability.
- Establish best practices for prompt engineering, model lifecycle management, and AI governance.
Security and Compliance- Implement AI security controls, including PII protection, prompt injection mitigation, and access controls.
- Ensure compliance with enterprise governance, auditing, and data management requirements.
- Develop secure and responsible AI solutions aligned with organizational standards.
Collaboration and Leadership- Partner with product, engineering, security, and data teams to define technical solutions and delivery roadmaps.
- Mentor junior engineers and promote engineering best practices.
- Lead technical design discussions and contribute to architecture decisions.
Required QualificationsMinimum Qualifications- Bachelor's degree in Computer Science, Engineering, Information Systems, or related field, or equivalent practical experience.
- 7+ years of software engineering experience developing enterprise applications.
- 5+ years of professional experience developing applications in Python.
- 3+ years of experience building and deploying machine learning or Generative AI solutions in production environments.
- Hands-on experience with LangChain and LangGraph for agent and workflow orchestration.
- Experience building RAG pipelines, including embeddings, vector databases, retrieval strategies, and evaluation frameworks.
- Experience developing APIs and microservices using FastAPI or similar Python frameworks.
- Experience with cloud platforms, preferably Google Cloud Platform and Vertex AI.
- Experience with Docker, Kubernetes, and CI/CD automation.
- Strong understanding of software architecture, distributed systems, and API design.
- Excellent communication and stakeholder management skills.
Preferred Qualifications- Experience with Vertex AI services, including Model Garden, Endpoints, Pipelines, and Vector Search.
- Experience with vector databases such as Pinecone, Weaviate, Milvus, or FAISS.
- Experience with React, Next.js, or modern front-end frameworks.
- Experience with GenAI evaluation tools such as RAGAS, G-Eval, LangSmith, or OpenTelemetry.
- Knowledge of AI security, governance, model monitoring, and responsible AI practices.
- Experience with LlamaIndex, Graph RAG, Knowledge Graphs, or advanced retrieval architectures.
- Experience integrating LLMs with enterprise data platforms, SaaS applications, or structured databases.
Technical SkillsRequired- Python (5+ years)
- LangChain
- LangGraph (1-2+ years)
- FastAPI
- Google Vertex AI
- RAG Architecture
- Vector Databases
- Docker
- Kubernetes
- CI/CD
Preferred- React / Next.js
- Node.js
- Pinecone
- Weaviate
- Milvus
- LlamaIndex
- OpenTelemetry
- LangSmith
- Google Cloud Platform Services
Compensation Details- Location: Charlotte, NC
- Work Arrangement: Hybrid (3 onsite / 2 remote)
This position is ideal for a hands-on AI engineering leader who thrives in building production-grade GenAI applications and driving enterprise AI adoption through scalable, secure, and high-impact solutions.
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