Highbrow LLC
AI / ML Engineer
Location: Dallas, TX
Description We are seeking an experienced AI/ML Engineer with strong expertise in Agentic AI systems and orchestration frameworks such as LangChain, CrewAI, Agno, combined with hands‑on experience in Machine Learning using Python for both textual and tabular data. The ideal candidate will have a solid background in cloud platforms, CI/CD pipelines, and secure agentic system design, along with practical knowledge of MLOps/LLMOps best practices. Experience with Telecom billing systems is a plus.
Qualifications We are seeking an experienced AI/ML Engineer with strong expertise in Agentic AI systems and orchestration frameworks such as LangChain, CrewAI, Agno, combined with hands‑on experience in Machine Learning using Python for both textual and tabular data. The ideal candidate will have a solid background in cloud platforms, CI/CD pipelines, and secure agentic system design, along with practical knowledge of MLOps/LLMOps best practices. Experience with Telecom billing systems is a plus.
Key Responsibilities
Agentic AI Development
Design and implement Agentic AI architectures using orchestration tools like LangChain, CrewAI, Agno.
Build secure, scalable multi‑agent systems for enterprise workflows.
Integrate LLMs and external APIs for dynamic reasoning and task execution.
Exposure to vector databases (Pinecone, Weaviate, Azure AI Search, Neo4j) and retrieval‑augmented generation (RAG).
Machine Learning & Data Handling
Develop ML models for text analytics (NLP, embeddings, transformers) and tabular data (classification, regression, clustering).
Optimize algorithms for performance and accuracy using Python and popular ML libraries (TensorFlow, PyTorch, Scikit‑learn).
Cloud & Deployment
Deploy AI/ML solutions on AWS, Azure, or GCP with best practices for scalability and security.
Implement CI/CD pipelines for automated testing, deployment, and monitoring of AI systems.
MLOps / LLMOps
Establish model lifecycle management, including versioning, monitoring, and retraining.
Implement LLMOps workflows for prompt management, evaluation, and fine‑tuning of large language models.
Security & Compliance
Design secure agentic systems with proper authentication, authorization, and data privacy controls.
Ensure compliance with enterprise security standards
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Description We are seeking an experienced AI/ML Engineer with strong expertise in Agentic AI systems and orchestration frameworks such as LangChain, CrewAI, Agno, combined with hands‑on experience in Machine Learning using Python for both textual and tabular data. The ideal candidate will have a solid background in cloud platforms, CI/CD pipelines, and secure agentic system design, along with practical knowledge of MLOps/LLMOps best practices. Experience with Telecom billing systems is a plus.
Qualifications We are seeking an experienced AI/ML Engineer with strong expertise in Agentic AI systems and orchestration frameworks such as LangChain, CrewAI, Agno, combined with hands‑on experience in Machine Learning using Python for both textual and tabular data. The ideal candidate will have a solid background in cloud platforms, CI/CD pipelines, and secure agentic system design, along with practical knowledge of MLOps/LLMOps best practices. Experience with Telecom billing systems is a plus.
Key Responsibilities
Agentic AI Development
Design and implement Agentic AI architectures using orchestration tools like LangChain, CrewAI, Agno.
Build secure, scalable multi‑agent systems for enterprise workflows.
Integrate LLMs and external APIs for dynamic reasoning and task execution.
Exposure to vector databases (Pinecone, Weaviate, Azure AI Search, Neo4j) and retrieval‑augmented generation (RAG).
Machine Learning & Data Handling
Develop ML models for text analytics (NLP, embeddings, transformers) and tabular data (classification, regression, clustering).
Optimize algorithms for performance and accuracy using Python and popular ML libraries (TensorFlow, PyTorch, Scikit‑learn).
Cloud & Deployment
Deploy AI/ML solutions on AWS, Azure, or GCP with best practices for scalability and security.
Implement CI/CD pipelines for automated testing, deployment, and monitoring of AI systems.
MLOps / LLMOps
Establish model lifecycle management, including versioning, monitoring, and retraining.
Implement LLMOps workflows for prompt management, evaluation, and fine‑tuning of large language models.
Security & Compliance
Design secure agentic systems with proper authentication, authorization, and data privacy controls.
Ensure compliance with enterprise security standards
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