What are the responsibilities and job description for the Technical Expert position at CloudIngest?
Technical Expert – Agentic AI & Enterprise Platforms
Location: Dallas, TX
Need senior resources with 13, 14, 15 years experienced
Key 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.