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Gen AI Engineer
Job in
Charlotte, Mecklenburg County, North Carolina, 28245, USA
Listed on 2026-07-25
Listing for:
IMCS Group
Full Time
position Listed on 2026-07-25
Job specializations:
-
Software Development
AI Engineer (Applied/Software), Machine Learning/ ML Engineer, Cloud Engineer - Software, DevOps
Job Description & How to Apply Below
Work Location:
Charlotte NC 28202 Hybrid – 3 days work from Office is Mandatory
F2F interview:
Yes (Mandatory)
- 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 MCP tools.
- 7+ years of hands‑on experience in AI, data science, ML, and Gen AI.
- 2+ years of strong hands‑on experience in Agentic AI, VLLM’s, Lang Chain, Lang Graph, RAG, LLMOps, and AI services in GCP and Azure.
- Strong experience designing and deploying Retrieval‑Augmented Generation (RAG) pipelines.
- Strong MLOps/LLMOps experience with CI/CD automation.
- Extensive experience with Lang Chain, Lang Graph, and agentic AI patterns including routing, memory, multi‑agent orchestration, guardrails, and failure recovery.
- Cloud‑native engineering across AWS (Sage Maker, Lambda, ECS/Fargate, S3, API Gateway, Step Functions) and GCP (Vertex AI) for scalable AI delivery.
- Developed microservices and API development using FastAPI, REST APIs, Pydantic/JSON schemas, Docker, and Kubernetes for low‑latency serving.
- Hands‑on experience with vector databases and semantic search technologies such as Pinecone, FAISS, ChromaDB, and embedding lifecycle management.
- Proficiency in Python and AI/ML frameworks (PyTorch, Tensor Flow).
- Experience using session and memory for building multi‑agent systems and MCP tools.
- Experience with LLMs, transformers, and the Hugging Face ecosystem.
- Strong experience in LLM fine‑tuning with LoRA, QLoRA, and PEFT.
- Expertise in architecting advanced RAG systems using Pinecone, FAISS, Weaviate, Chroma, hybrid retrieval, and custom embeddings.
- Designing end‑to‑end LLMOps/MLOps pipelines using MLflow, DVC, Sage Maker Pipelines, Vertex AI Pipelines, and Git Hub Actions.
- Experience with cloud‑native AI systems on AWS (Sage Maker, Lambda, EKS, EC2, Step Functions, S3, Glue) and GCP Vertex AI.
- Developed multi‑agent orchestration workflows using Lang Graph and CrewAI for tool‑calling, validation agents, automated reasoning, and workflow supervision.
- Minimum years: >10 years.
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