Senior Technology Architect Generative AI / Machine Learning
Irving, Texas, United States of America
Contract
2 days ago
$70 - $72 USD
Key skills
PythonAIMachine LearningMLGenerative AIGenAILLMRAGLangChainAgenticPyTorchTensorFlowHugging FaceMLOpsMLflowLangGraphPineconeWeaviateFastAPIAWSGoogle CloudKubernetesDockerEKSLambdaS3SageMakerVertex AICI/CDStakeholder ManagementCommunication
About this role
Job Title: Senior Technology Architect Generative AI / Machine Learning
< class="x_elementToProof">Location: Irving, TX (Onsite/Hybrid)Duration: 12 Months Contract
Role Overview:
We are seeking a Senior Technology Architect specializing in Generative AI and Machine Learning to lead the design and deployment of next-generation AI solutions. This role focuses on building scalable LLM-powered applications, Agentic AI systems, and Retrieval-Augmented Generation (RAG) pipelines for enterprise use cases.
You will play a critical role in architecting end-to-end AI platforms, integrating GenAI into business workflows, and driving innovation using modern AI frameworks and cloud-native technologies.
Key Responsibilities
- Architect and develop Generative AI solutions for text, image, and multimodal applications
- Design and implement RAG pipelines using vector databases and embedding strategies
- Build and deploy Agentic AI systems with multi-agent orchestration, memory, and tool usage
- Develop prompt engineering frameworks and optimize LLM performance
- Integrate AI capabilities into enterprise applications and microservices architectures
- Lead LLMOps/MLOps pipelines including CI/CD automation, monitoring, and governance
- Collaborate with cross-functional teams to translate business needs into AI-driven solutions
- Ensure scalability, reliability, and performance of AI systems in production environments
Required Skills & Qualifications
- 10+ years of experience in AI/ML, Data Science, or related fields
- Strong expertise in Generative AI, LLMs, and Transformer-based models
- Hands-on experience with RAG (Retrieval-Augmented Generation) and semantic search
- Proficiency in Python and ML frameworks such as PyTorch or TensorFlow
- Extensive experience with:
- LangChain, LangGraph, CrewAI (multi-agent orchestration)
- Vector databases: Pinecone, FAISS, ChromaDB, Weaviate
- Embeddings and retrieval strategies
- Strong experience in LLMOps/MLOps (MLflow, DVC, CI/CD pipelines)
- Experience building APIs & microservices using FastAPI, REST, Docker, Kubernetes
- Hands-on experience with LLM fine-tuning (LoRA, QLoRA, PEFT)
- Experience with Hugging Face ecosystem and transformer models
Cloud & Platform Experience
- Experience with Google Cloud Platform (Google Cloud Platform) especially Vertex AI
- Exposure to AWS services (SageMaker, Lambda, EKS, S3)
- Experience deploying scalable AI systems in cloud-native environments
Nice to Have
- Experience with Prompt Engineering best practices
- Knowledge of multi-modal AI systems
- Familiarity with enterprise AI governance and security
- Experience with real-time inference and high-throughput systems
Top 3 Responsibilities
- Lead design and implementation of GenAI & Agentic AI architectures
- Build scalable RAG-based AI solutions for enterprise use cases
- Drive LLMOps/MLOps best practices for production-ready AI systems
Soft Skills
- Strong communication and stakeholder management skills
- Ability to lead technical discussions and mentor teams
- Problem-solving mindset with a focus on innovation