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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
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.
- 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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