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GEN AI engineer

Absolute IT

 

Charlotte, North Carolina, United States

Posted On: 30+ days ago
Experience: 7+ years
Availability: Hybrid
Openings: 1
Category: Gen AI Engineer
Tenure: Contract - Corp-to-Corp
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Description

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 MCP 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

Education

Bachelor's degree

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