AI/ML Engineer
Diverse Lynx
Job Title: Senior Technology Architect | Cloud Platform | Google Machine Learning Work Location: Irving,TX 75039 Contract duration: 12 + months Job Details: Must Have Skills GEN AI, Agentic AI Cortex AI,, 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 MCP tools.
- 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 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 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
Vacancy posted 4 days ago
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