Experience deploying and operating model- serving or MCP – like server infrastructure (selfhosted or managed). Production experience with vector databases and designing ingestion + embedding pipelines for both batch and streaming workloads.
Numbers & Facts
Location
Plano, TX
Job Type
Full-time
Description
Benefits:
Bonus based on performance
Dental insurance
Health insurance
Vision insurance
Qualifications
Bachelor’s Degree
6+ years cloud architecture experience
3+ years building production GenAI/LLM systems on AWS.
Strong Python and AWS expertise, including Lambda, ECS/EKS, S3, SageMaker, Docker and Kubernetes.
Production experience with vector databases and designing ingestion + embedding pipelines for both batch and streaming workloads.
Hands-on with prompt design, evaluation, LLM orchestration, and RAG implementation patterns.
Experience deploying and operating model- serving or MCP – like server infrastructure (selfhosted or managed).
Proficient with IaC and delivery tooling, including Terraform/CloudFormation, GitOps, and CI pipelines.
Experience with model-serving infrastructure, such as Amazon SageMaker, NVIDIA Triton, Ray Serve, or similar platforms.
Hands-on experience with GenAI libraries and frameworks, including LangChain, LlamaIndex, Hugging Face, and OpenAI APIs.
Deep operational expertise with vector databases, such as Pinecone, Milvus, Weaviate, or Qdrant.
AWS Solutions Architect, AWS DevOps Engineer, or equivalent industry certifications.