Job Description
Job Title: Generative AI Engineer
Work Location & Reporting Address: Charlotte, NC 28202 (Onsite-Hybrid. LOCAL CANDIDATES ONLY!!!)
Contract duration: 12 Months
Interview Mode- In-person Interview
Must Have Skills:
- GEN AI
- Agentic AI
- VLLM
- fAST API
- REST API
- ClientD
- Lang Graph
- Lang Chain
- Graph RAG
- ML Ops
- Python
- ML
- Data Science
- RAG
- LLM
Nice to Have Skills:
- GCP
- Prompt Engineering
Detailed Job Description:
- We are seeking a highly skilled Generative AI Engineer with a strong Python background to design, develop, and deploy cutting-edge AI solutions. The ideal candidate will have hands-on experience with Large Language Models (LLMs), prompt engineering, and Gen AI frameworks, along with expertise in building scalable AI applications. Experience in Developing Agentic AI solutions.
Key Responsibilities:
- Design and implement Generative AI models for text, image, or multimodal applications.
- Develop prompt engineering strategies and embedding-based retrieval systems.
- Integrate Gen AI capabilities into web applications and enterprise workflows.
- Build agentic AI applications with context engineering and ClientP tools.
Required Skills & Qualifications:
- 7 years of hands-on experience in AI, Data science, ML, GEN AI
- 2 years of strong hands on experience in Agentic AI, VLLM s, GEN AI, Lang Chain, Lang Graph, RAG, LLM OPS and AI Services in GCP and Azure.
- Strong hands on experience designing and deploying Retrieval-Augmented Generation (RAG) pipelines
- Strong MLOps/LLMOps experience with CI/CD automation,
- Extensive experience with LangChain, LangGraph, and agentic AI patterns including routing, memory, multi-agent orchestration, guardrails, and failure recovery.
- Experience in Cloud-native engineering across AWS (SageMaker, Lambda, ECS/Fargate, S3, API Gateway, Step Functions) and GCP (Vertex AI) for scalable AI delivery
- Experience in Developing microservices and API development using FastAPI, REST APIs, Pydantic/JSON schemas, Docker, and Kubernetes for low-latency serving.
- Strong Hands-on experience with vector databases and semantic search technologies including Pinecone, FAISS, ChromaDB, and embedding lifecycle management
- Strong proficiency in Python and AI/ML frameworks (PyTorch, TensorFlow).
- Hands on experience using session and memory for building multi-agent systems along with using ClientP tools.
- Hands-on experience with LLMs, transformers, and Hugging Face ecosystem.
- Knowledge and experience with vector databases and RAG technique for semantic search.
- Familiarity with cloud AI services (AWS SageMaker, Azure OpenAI, GCP Vertex AI).
- Understanding of MLOps practices for scalable AI deployment.
- Strong experience in working with LLM fine-tuning with LoRA, QLoRA, PEFT,
- Strong experience in Architected advanced RAG systems using Pinecone, FAISS, Weaviate, Chroma, hybrid retrieval, and custom embeddings,
- Strong experience in Designing end-to-end LLMOps/MLOps pipelines using MLflow, DVC, SageMaker Pipelines, Vertex AI Pipelines, and GitHub Actions
- Experience in using cloud-native AI systems on AWS (SageMaker, Lambda, EKS, EC2, Step Functions, S3, Glue) and GCP Vertex AI, supporting high-volume inference and secure enterprise operations
- Experience in developing multi-agent orchestration workflows using LangGraph and CrewAI for tool-calling, validation agents, automated reasoning, and workflow supervision
- Minimum Years of Experience:-10 years
Numbers & Facts
| Location | Charlotte, NC |
| Industry | Other/Not Classified |
| Company Size | 100 to 499 employees |
| Year Founded | 1998 |
| Website | www.eteaminc.com |
About Company
Looking for a great job? Join eTeam. We’re looking for talented staffing professionals to join our staff. We also provide contract assignments and full-time jobs at Fortune 2000 Companies. We’ve been named one of the best companies to work for by Staffing Industry Analysts and New Jersey Business.
Skills
- AWS Lambdaunmatched
- Amazon Elastic Compute Cloud (EC2)unmatched
- Amazon Simple Storage Service (S3)unmatched
- Amazon Web Services (AWS)unmatched
- Application Programming Interface (API)unmatched
- Artificial Intelligence (AI)unmatched
- Artificial Intelligence (AI) Programming Languagesunmatched
- Automationunmatched
- Cloud Computingunmatched
- Continuous Deployment/Deliveryunmatched
- Continuous Integrationunmatched
- Data Scienceunmatched
- Dockerunmatched
- Ecosystemsunmatched
- GCP (Good Clinical Practices)unmatched
- GitHubunmatched
- Internet Applicationunmatched
- JSONunmatched
- Leading Edge Technologyunmatched
- Memory Hardwareunmatched
- Microservicesunmatched
- Microsoft Windows Azureunmatched
- Modeling Languagesunmatched
- Operations Security (OPSEC)unmatched
- Python Programming/Scripting Languageunmatched
- REST (Representational State Transfer)unmatched
- Scalable System Developmentunmatched
- Search Technologyunmatched
- Semantic Searchunmatched
- Software Engineeringunmatched
- Strategic Planningunmatched
- System Architectureunmatched
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