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Lead AI / GenAI Engineer Nearest Client Office USA_hybrid

BURGEON IT SERVICES LLCDallas, TX🇺🇸United StatesPosted 13 Aug 2026

Quick Overview

Work Type
Hybrid
Level
Mid Senior

Job Description

Lead AI / GenAI Engineer
Location: Nearest Client Office USA_hybrid
Duration: 12 Months plus Contract
Experience: 8 12+ Years

Please share your updated resume with me at pranayatburgeonitsdotcom
Role Overview
We are looking for a Lead AI / GenAI Engineer to lead the technical strategy and development of production-grade AI/LLM systems. The ideal candidate will be hands-on with Python, RAG, agentic AI, ML frameworks, data engineering, and cloud technologies.
Mandatory Skills
  • 8+ years of software engineering experience with strong recent hands-on development.
  • 3+ years hands-on experience in Machine Learning, Data Science, Search/Relevance, or Ranking systems.
  • Strong Python development experience.
  • Production experience with AI/LLM/GenAI systems.
  • Strong experience with RAG, retrieval, orchestration, AI agents, and evaluation systems.
  • Experience with LangChain and/or LangGraph.
  • Strong knowledge of ML frameworks: PyTorch, TensorFlow, Scikit-learn, and/or MLflow.
  • Strong Pandas and NumPy skills.
  • Experience building REST APIs and scalable backend services.
  • Strong SQL and experience working with large-scale structured/unstructured data.
  • Experience with AWS and/or Google Cloud Platform, preferably AWS Bedrock.
  • Experience with Vector Databases such as Qdrant.
  • Knowledge of Kubernetes and Docker.
  • Experience with Kafka / event-driven architectures.
  • Experience with CI/CD, Git, automated testing, and production deployment.
  • Strong understanding of data preprocessing, feature engineering, data validation, transformation, modeling, and storage.
  • Bachelor's degree in Computer Science, Engineering, Data Science, or related quantitative field.
Preferred
  • Experience designing AI systems at scale, including latency, cost, observability, safety, and responsible AI.
  • Experience with ML model deployment and inference pipelines.
  • Experience mentoring junior AI/ML engineers.
  • Experience leading AI technical strategy across multiple products.

Skills

Docker
SQL
AWS
MLflow
Machine Learning
NumPy
Scikit-learn
Git
Google Cloud
Kafka
Kubernetes
LLM
Pandas
PyTorch
Python
REST
TensorFlow

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