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AI/ML Engineer

Raas Infotek LLCDallas, TX🇺🇸United StatesPosted 3 Aug 2026

Why This Role Stands Out

This on-site AI/ML Engineer role offers a significant opportunity to shape enterprise-scale solutions using cutting-edge Generative AI and LLMs, perfect for a seasoned professional with 15+ years of IT experience and deep expertise in Python and MLOps. You'll collaborate with dynamic teams to deliver impactful, production-ready innovations. Apply now to leverage your extensive skills and drive technological advancement.

Quick Overview

Work Type
On Site
Level
Mid Senior

Job Description

AI/ML Engineer (15+ Years Experience Required)


🏢 Work Model: Onsite
💼 Employment Type: W2 Only

Job Summary

We are seeking a highly experienced AI/ML Engineer with 15+ years of IT experience to design, develop, and deploy enterprise-scale Artificial Intelligence and Machine Learning solutions. The ideal candidate will have strong expertise in Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Python, cloud platforms, and MLOps. This role requires hands-on experience building scalable AI applications and collaborating with cross-functional teams to deliver innovative, production-ready solutions.

Required Qualifications

  • 15+ years of overall IT experience.
  • Bachelor''s or Master''s degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
  • Strong programming experience in Python.
  • Hands-on experience with Machine Learning and Deep Learning frameworks such as TensorFlow or PyTorch.
  • Experience building applications using Large Language Models (LLMs).
  • Strong knowledge of Generative AI technologies.
  • Experience with Retrieval-Augmented Generation (RAG) architectures.
  • Hands-on experience with LangChain and/or LangGraph.
  • Experience with OpenAI, Azure OpenAI, AWS Bedrock, Anthropic Claude, or Google Vertex AI.
  • Experience working with vector databases such as Pinecone, FAISS, ChromaDB, Milvus, or Weaviate.
  • Strong knowledge of NLP, embeddings, prompt engineering, and AI model integration.
  • Experience developing and consuming REST APIs.
  • Hands-on experience with Docker and Kubernetes.
  • Experience with AWS, Azure, or Google Cloud Platform.
  • Knowledge of MLOps, model deployment, monitoring, and CI/CD pipelines.
  • Experience with Git and Agile/Scrum methodologies.

Preferred Skills

  • Experience with Hugging Face Transformers.
  • Knowledge of Databricks, Snowflake, or Apache Spark.
  • Experience with AI governance, Responsible AI, and model evaluation.
  • Familiarity with multi-agent AI frameworks and AI orchestration.
  • Excellent analytical, problem-solving, and communication skills.

Responsibilities

  • Design, develop, and deploy enterprise AI/ML solutions.
  • Build scalable Generative AI and LLM-based applications.
  • Develop RAG pipelines using vector databases and modern AI frameworks.
  • Fine-tune, evaluate, and optimize machine learning models.
  • Integrate AI solutions with enterprise applications and APIs.
  • Deploy AI workloads using cloud-native technologies and MLOps best practices.
  • Collaborate with architects, data scientists, and software engineers to deliver high-quality AI solutions.
  • Ensure security, scalability, performance, and reliability of AI applications.
  • Stay current with emerging AI technologies and recommend innovative solutions.

Required Technical Skills

  • Python
  • Machine Learning
  • Deep Learning
  • Generative AI
  • Large Language Models (LLMs)
  • RAG (Retrieval-Augmented Generation)
  • LangChain / LangGraph
  • OpenAI / Azure OpenAI / AWS Bedrock / Vertex AI
  • TensorFlow / PyTorch
  • Hugging Face
  • Vector Databases (Pinecone, FAISS, ChromaDB, Milvus, Weaviate)
  • Docker
  • Kubernetes
  • AWS / Azure / Google Cloud Platform
  • Git
  • REST APIs
  • CI/CD
  • MLOps

Skills

Docker
AWS
MLOps
Machine Learning
NLP
Scrum
Snowflake
Agile
Apache
Apache Spark
Azure
Databricks
Deep Learning
Generative AI
Git
Google Cloud
Hugging Face
Kubernetes
LLM
PyTorch
Python
REST
TensorFlow

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