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Agentic AI & Enterprise Platforms
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cloudingest inc
Dallas, TX (In Person)
Full-Time
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Job Description
Responsibilities Architect and develop enterprise-grade Agentic AI , Generative AI , and Machine Learning solutions. Design and implement intelligent workflows, multi-agent systems, and AI orchestration frameworks. Build and optimize custom machine learning models for classification, prediction, segmentation, recommendation, and analytics use cases. Lead development of RAG (Retrieval-Augmented Generation) , semantic search, and knowledge retrieval solutions. Design scalable data pipelines leveraging Snowflake, Databricks, and cloud-native technologies. Develop and deploy AI services, APIs, and microservices for production environments. Define architecture standards, coding best practices, governance, security, and performance guidelines. Mentor developers, conduct design reviews, and drive technical excellence across teams. Evaluate emerging AI technologies and recommend adoption strategies. Required Qualifications Bachelor s or Master s degree in Computer Science, Engineering, Data Science, or a related field. 10+ years of experience in software engineering, solution architecture, or platform engineering. 5+ years of experience building AI/ML solutions in enterprise environments. Strong hands-on programming experience in Python. Proven experience leading architecture and development of large-scale distributed systems. Technical Skills AI / Machine Learning Generative AI and Large Language Models (LLMs) Agentic AI and Multi-Agent Systems RAG Architecture and Semantic Search Prompt Engineering Fine-Tuning and Model Evaluation Custom ML Model Development Machine Learning Techniques Classification Models Clustering Models Recommendation Systems Predictive Analytics Feature Engineering MLOps and Model Lifecycle Management Frameworks & Libraries LangGraph AutoGen LangChain CrewAI (preferred) MCP (Model Context Protocol) OpenAI APIs Anthropic Claude APIs Hugging Face Ecosystem Scikit-Learn XGBoost PyTorch TensorFlow (preferred) Data & Analytics Platforms Snowflake Databricks SQL Data Engineering Vector Databases Feature Stores Data Warehousing Concepts Backend & APIs Python Flask REST APIs FastAPI (good to have) Microservices Architecture Event-Driven Architecture Cloud & DevOps Microsoft Azure Azure Kubernetes Service (AKS) Docker Kubernetes CI/CD Pipelines Azure DevOps GitHub Front-End (Good to Have) React Angular Preferred Experience Building enterprise AI assistants and conversational platforms. Developing AI-powered analytics and decision-support systems. Designing agent orchestration frameworks and workflow automation platforms. Working with telecom, marketing analytics, customer intelligence, or large-scale enterprise datasets. Experience handling datasets with millions of records and deploying AI solutions at scale. Exposure to AI governance, responsible AI, and model monitoring frameworks.