

Senior AI Generative Engineering Lead
β - Featured Role | Apply direct with Data Freelance Hub
This role is for a Senior AI Generative Engineering Lead in Houston, TX (Hybrid, 3 days onsite), with a contract length and pay of $58.00 per hour. Requires 5+ years in software development, expertise in Generative AI, and proficiency in Python and cloud platforms.
π - Country
United States
π± - Currency
$ USD
-
π° - Day rate
464
-
ποΈ - Date discovered
September 17, 2025
π - Project duration
Unknown
-
ποΈ - Location type
Hybrid
-
π - Contract type
Unknown
-
π - Security clearance
Unknown
-
π - Location detailed
Houston, TX 77008
-
π§ - Skills detailed
#Docker #GIT #Langchain #Automation #Documentation #ML (Machine Learning) #Cloud #Scala #Monitoring #Microservices #Azure #Version Control #Infrastructure as Code (IaC) #YAML (YAML Ain't Markup Language) #Security #Azure DevOps #Kubernetes #AI (Artificial Intelligence) #Computer Science #Leadership #GCP (Google Cloud Platform) #Compliance #DevOps #Databases #API (Application Programming Interface) #Python #Deployment #Terraform
Role description
Role : Generative AI Engineer
Location : Houston, TX ( Hybrid , 3 days onsite )
Job description:
We are seeking a highly skilled Applied AI Engineer to join our Data & AI team. This role is ideal for an engineer with deep expertise in Generative AI (GenAI) technologies and a proven track record of delivering production-grade AI solutions. The Applied AI Engineer will design, build, and scale GenAI applications, while also contributing to enterprise standards, reusable frameworks, and the overall maturity of our AI engineering practices.
This position requires someone who can balance hands-on solution delivery with technical leadership in design, integration, and optimization, ensuring our AI initiatives deliver measurable business impact.
Key Responsibilities
Solution Engineering & Delivery
Translate business requirements into robust, scalable AI solutions using RAG, embeddings, vector search, and fine-tuning.
Design, prototype, and implement LLM-driven applications with multi-step agent workflows and orchestration frameworks (e.g., LangGraph, LangChain, LlamaIndex).
Build and maintain APIs, services, and reusable components in Python to support AI applications.
Deploy and monitor AI models in cloud-native environments (GCP, Azure) leveraging Kubernetes, serverless, and MLOps pipelines.
Continuously evaluate model/system performance and implement improvements.
Architecture & Standards
Contribute to the design of modular and reusable AI architectures across projects.
Establish and follow engineering best practices for GenAI development, testing, deployment, and monitoring.
Support the creation of documentation, templates, and playbooks for consistent solution delivery.
Collaboration & Integration
Partner with cross-functional teams to integrate AI capabilities into enterprise applications.
Work closely with business stakeholders to translate challenges into AI-powered solutions.
Share lessons learned and help drive adoption of AI practices across teams.
Ensure AI applications align with security, compliance, and responsible AI standards.
Working Conditions
Hybrid work model: Onsite in Houston office 3 days per week.
Open, collaborative team environment.
Minimum Requirements
Bachelorβs or Masterβs degree in Computer Science, AI/ML, or related technical field.
5+ years of software development experience, with strong proficiency in Python.
3β5+ years hands-on experience building GenAI/LLM-based applications, with proven success from PoC to production deployment.
Proficiency in designing retrieval pipelines (document loaders, chunking strategies, embeddings, vector databases like FAISS, Pinecone, ChromaDB).
Expertise in LLM APIs (OpenAI, Claude, Gemini, etc.), prompt engineering, and fine-tuning.
Experience with cloud platforms (GCP, Azure), containerization (Docker, Kubernetes), and MLOps (CI/CD, monitoring).
Strong understanding of API design, microservices, and enterprise integration patterns.
Familiarity with version control systems (e.g., Git, Azure DevOps).
Demonstrated ability to build and scale AI solutions in production.
Preferred Qualifications
Experience with orchestration frameworks (LangGraph, LangChain, LlamaIndex).
Familiarity with DevOps practices such as IaC (Terraform), YAML pipelines, and automation.
Strong communication skills with ability to collaborate across teams and articulate technical concepts clearly.
Proactive, self-motivated problem solver with a track record of delivering high-value solutions.
Leverage vibe and agentic coding tools such as Cursor, Claude Code, and similar frameworks to accelerate AI solution development and orchestrate multi-agent workflows.
Additional Attributes
Analytical mindset with focus on measurable outcomes.
Collaborative team player who thrives in cross-functional environments.
Curiosity and drive to stay current with emerging GenAI technologies.
Job Type: Contract
Pay: From $58.00 per hour
Experience:
Generative AI Engineer: 1 year (Required)
scalable AI solutions : 1 year (Required)
Python: 1 year (Required)
Google Cloud Platform: 1 year (Required)
Azure: 1 year (Required)
MLOps: 1 year (Required)
integrate AI : 1 year (Required)
GenAI/LLM-based applications: 1 year (Required)
Location:
Houston, TX 77002 (Required)
Work Location: In person
Role : Generative AI Engineer
Location : Houston, TX ( Hybrid , 3 days onsite )
Job description:
We are seeking a highly skilled Applied AI Engineer to join our Data & AI team. This role is ideal for an engineer with deep expertise in Generative AI (GenAI) technologies and a proven track record of delivering production-grade AI solutions. The Applied AI Engineer will design, build, and scale GenAI applications, while also contributing to enterprise standards, reusable frameworks, and the overall maturity of our AI engineering practices.
This position requires someone who can balance hands-on solution delivery with technical leadership in design, integration, and optimization, ensuring our AI initiatives deliver measurable business impact.
Key Responsibilities
Solution Engineering & Delivery
Translate business requirements into robust, scalable AI solutions using RAG, embeddings, vector search, and fine-tuning.
Design, prototype, and implement LLM-driven applications with multi-step agent workflows and orchestration frameworks (e.g., LangGraph, LangChain, LlamaIndex).
Build and maintain APIs, services, and reusable components in Python to support AI applications.
Deploy and monitor AI models in cloud-native environments (GCP, Azure) leveraging Kubernetes, serverless, and MLOps pipelines.
Continuously evaluate model/system performance and implement improvements.
Architecture & Standards
Contribute to the design of modular and reusable AI architectures across projects.
Establish and follow engineering best practices for GenAI development, testing, deployment, and monitoring.
Support the creation of documentation, templates, and playbooks for consistent solution delivery.
Collaboration & Integration
Partner with cross-functional teams to integrate AI capabilities into enterprise applications.
Work closely with business stakeholders to translate challenges into AI-powered solutions.
Share lessons learned and help drive adoption of AI practices across teams.
Ensure AI applications align with security, compliance, and responsible AI standards.
Working Conditions
Hybrid work model: Onsite in Houston office 3 days per week.
Open, collaborative team environment.
Minimum Requirements
Bachelorβs or Masterβs degree in Computer Science, AI/ML, or related technical field.
5+ years of software development experience, with strong proficiency in Python.
3β5+ years hands-on experience building GenAI/LLM-based applications, with proven success from PoC to production deployment.
Proficiency in designing retrieval pipelines (document loaders, chunking strategies, embeddings, vector databases like FAISS, Pinecone, ChromaDB).
Expertise in LLM APIs (OpenAI, Claude, Gemini, etc.), prompt engineering, and fine-tuning.
Experience with cloud platforms (GCP, Azure), containerization (Docker, Kubernetes), and MLOps (CI/CD, monitoring).
Strong understanding of API design, microservices, and enterprise integration patterns.
Familiarity with version control systems (e.g., Git, Azure DevOps).
Demonstrated ability to build and scale AI solutions in production.
Preferred Qualifications
Experience with orchestration frameworks (LangGraph, LangChain, LlamaIndex).
Familiarity with DevOps practices such as IaC (Terraform), YAML pipelines, and automation.
Strong communication skills with ability to collaborate across teams and articulate technical concepts clearly.
Proactive, self-motivated problem solver with a track record of delivering high-value solutions.
Leverage vibe and agentic coding tools such as Cursor, Claude Code, and similar frameworks to accelerate AI solution development and orchestrate multi-agent workflows.
Additional Attributes
Analytical mindset with focus on measurable outcomes.
Collaborative team player who thrives in cross-functional environments.
Curiosity and drive to stay current with emerging GenAI technologies.
Job Type: Contract
Pay: From $58.00 per hour
Experience:
Generative AI Engineer: 1 year (Required)
scalable AI solutions : 1 year (Required)
Python: 1 year (Required)
Google Cloud Platform: 1 year (Required)
Azure: 1 year (Required)
MLOps: 1 year (Required)
integrate AI : 1 year (Required)
GenAI/LLM-based applications: 1 year (Required)
Location:
Houston, TX 77002 (Required)
Work Location: In person