AIML Solution Architect
Job Location:
Dallas, IA - USA
Monthly Salary:
Not Disclosed
Posted on:
10 hours ago
Vacancies:
1 Vacancy
Job Summary
Top 3 Mandatory Skills and Experience:
1) 10 years software architecture experience with at least 3 years designing AI/ML platform systems including hands-on experience with LLM orchestration frameworks (LangChain LangGraph Semantic Kernel or similar).
2) Deep expertise in distributed systems design microservices architecture event-driven patterns and API design (REST/gRPC) with strong proficiency in Python and at least one of Java/Go/TypeScript.
3) Production experience building and deploying agentic AI systems or LLM-powered applications at scale including prompt engineering tool-use patterns RAG pipelines and agent reliability/observability.
Nice to Have Skills:
Experience with Kubernetes/container orchestration cloud platforms (AWS/Azure/GCP) MLOps/LLMOps tooling vector databases (Pinecone Weaviate pgvector) knowledge graphs airline/travel domain experience TOGAF or similar architecture certification experience with multi-agent system design patterns and agent evaluation/benchmarking frameworks.
1) 10 years software architecture experience with at least 3 years designing AI/ML platform systems including hands-on experience with LLM orchestration frameworks (LangChain LangGraph Semantic Kernel or similar).
2) Deep expertise in distributed systems design microservices architecture event-driven patterns and API design (REST/gRPC) with strong proficiency in Python and at least one of Java/Go/TypeScript.
3) Production experience building and deploying agentic AI systems or LLM-powered applications at scale including prompt engineering tool-use patterns RAG pipelines and agent reliability/observability.
Nice to Have Skills:
Experience with Kubernetes/container orchestration cloud platforms (AWS/Azure/GCP) MLOps/LLMOps tooling vector databases (Pinecone Weaviate pgvector) knowledge graphs airline/travel domain experience TOGAF or similar architecture certification experience with multi-agent system design patterns and agent evaluation/benchmarking frameworks.