AI/ML Engineer (Agentic AI & GenAI)
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Description
Role:AI/ML Engineer (Agentic AI & GenAI) Location: Dallas, TX (Hybrid/Onsite Preferred)
Duration: Long-Term Contract Employment Type: W2 Only
Position: AI/ML Engineer Job Description We are seeking a highly skilled AI/ML Engineer with expertise in building Agentic AI systems, LLM-powered applications, and modern data platforms. The ideal candidate will be responsible for designing, developing, and deploying scalable AI solutions using LangGraph, MCP (Model Context Protocol), Python, FastAPI, Azure, Databricks, and Snowflake. The candidate should possess strong experience in AI orchestration frameworks, tool-calling architectures, agent workflows, and enterprise-scale data engineering environments. Key Responsibilities
Duration: Long-Term Contract Employment Type: W2 Only
Position: AI/ML Engineer Job Description We are seeking a highly skilled AI/ML Engineer with expertise in building Agentic AI systems, LLM-powered applications, and modern data platforms. The ideal candidate will be responsible for designing, developing, and deploying scalable AI solutions using LangGraph, MCP (Model Context Protocol), Python, FastAPI, Azure, Databricks, and Snowflake. The candidate should possess strong experience in AI orchestration frameworks, tool-calling architectures, agent workflows, and enterprise-scale data engineering environments. Key Responsibilities
- Design and develop Agentic AI applications using LangGraph and LLM orchestration frameworks.
- Build and manage multi-agent workflows, tool calling, memory management, and reasoning pipelines.
- Develop scalable APIs and AI services using Python and FastAPI.
- Implement MCP (Model Context Protocol) integrations to enable agent interoperability and external tool communication.
- Build Retrieval-Augmented Generation (RAG) solutions leveraging enterprise data sources.
- Integrate AI applications with enterprise platforms including Snowflake and Databricks.
- Design and optimize orchestration workflows for AI agents and business processes.
- Deploy and manage AI solutions on Microsoft Azure.
- Collaborate with business stakeholders to translate requirements into AI-driven solutions.
- Ensure AI applications comply with enterprise security, governance, and scalability standards.
- Perform performance tuning, prompt optimization, and model evaluation.
- Create reusable frameworks and best practices for AI application development.
- LangGraph
- Agentic AI Systems
- Tool Calling
- Multi-Agent Architecture
- MCP (Model Context Protocol)
- RAG Architecture
- Prompt Engineering
- LLM Orchestration
- Python
- FastAPI
- REST APIs
- Async Programming
- Microsoft Azure
- Azure OpenAI
- Azure AI Services
- Databricks
- Snowflake
- ETL/ELT Pipelines
- Data Modeling
- Data Integration
- Structured and Unstructured Data Processing
- Workflow Orchestration
- Agent Coordination
- Event-Driven Architectures
- API Integrations
- Experience with OpenAI, Azure OpenAI, Anthropic, or Gemini models.
- Experience building enterprise GenAI platforms.
- Knowledge of vector databases and semantic search.
- Experience with MLflow, MLOps, and model lifecycle management.
- Experience with Kubernetes and containerized deployments.
- Strong understanding of data governance, security, and compliance.
- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related field.
- 8+ years of software/data engineering experience.
- 3+ years of AI/ML or Generative AI development experience.
- Hands-on experience building production-grade Agentic AI solutions.
- Strong expertise in Python, Azure, Databricks, Snowflake, and modern AI orchestration frameworks.
- Excellent communication and stakeholder management skills.
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