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.

Requirements:

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.

• 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