Generative AI Engineer (Agentic AI & LLMs)

Generative AI Engineer (Agentic AI & LLMs)

Location: Charlotte, NC 28202 (Onsite) Duration: 12 Months In person Interview - Mandatory (2nd Round)

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:

• 10+ years of hands-on experience in AI, Data science, ML, GEN AI.
• Strong hands on experience designing and deploying Retrieval-Augmented Generation (RAG) pipelines
• Strong hands on experience with RAG pipelines and vector databases
• Extensive experience with LangChain, LangGraph, CrewAI, multi-agent orchestration
• Strong MLOps / LLMOps experience with CI/CD automation
• Experience across AWS (SageMaker, Lambda, EKS, S3) and GCP (Vertex AI)
• API & microservices development using FastAPI, REST, Docker, Kubernetes
• Strong Python proficiency with PyTorch / TensorFlow
• Extensive experience with LangChain, LangGraph, and agentic AI patterns including routing, memory, multi-agent orchestration, guardrails, and failure recovery.
• 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

Must Have Skills: GEN AI, Agentic AI Cortex AI, ML Ops, Python, ML, Data Science, RAG, LLM

Nice to have skills: GCP, Prompt Engineering

Minimum years of experience: > 10 years