mroads

Full Stack GenAI Engineer

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Full Stack GenAI Engineer in Plano, TX, offering a contract length of "unknown" at a pay rate of "unknown." Requires 10+ years in software engineering, proficiency in Python/JAVA, and expertise in GenAI applications and cloud platforms.
🌎 - Country
United States
πŸ’± - Currency
$ USD
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πŸ’° - Day rate
Unknown
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πŸ—“οΈ - Date
November 18, 2025
πŸ•’ - Duration
Unknown
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🏝️ - Location
On-site
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πŸ“„ - Contract
Unknown
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πŸ”’ - Security
Unknown
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πŸ“ - Location detailed
Plano, TX
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🧠 - Skills detailed
#Programming #Azure #Libraries #Java #GCP (Google Cloud Platform) #Kubernetes #AWS (Amazon Web Services) #Hugging Face #AI (Artificial Intelligence) #Python #"ETL (Extract #Transform #Load)" #Cloud #MLflow #Transformers #SageMaker #Docker #Microservices #ML (Machine Learning) #Databases #Langchain
Role description
mroads is looking for a "Full Stack GenAI Engineer" for one of the direct clients in Plano, TX. Requirements: β€’ 10+ years of software engineering and development experienceο‚· Proven experience in building and deploying GenAI applications in production. β€’ Strong programming skills in Python/JAVA and familiarity with GenAI libraries (Transformers, LangChain, Hugging Face, etc.). β€’ Deep understanding of LLMs, embeddings, vector databases (e.g., FAISS, Pinecone, Weaviate). β€’ Experience with cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes). β€’ Familiarity with CI/CD for ML workflows and versioning tools like MLflow or DVC. β€’ Knowledge of prompt engineering, few-shot learning, and agent-based systems. β€’ Hands-on experience designing and building cloud-native solutions (preferably on AWS) β€’ Experience with modern architecture styles: microservices, APIs, event-driven systems β€’ Strong ability to articulate technical solutions, trade-offs, and system behavior to both technical and non-technical stakeholders. Preferred Skills: β€’ Exposure to GenAI tools and frameworks (e.g., LLMs, vector databases, prompt orchestration, LangChain, Bedrock). β€’ Familiarity with AWS AI/ML services (e.g., SageMaker, Bedrock, Comprehend, Lex). β€’ AWS AI certification. β€’ Financial Services experience.