Cognizant
Position
Job Title:
AI Architect
Location:
Grand Rapids, MI - Hybrid
Role Overview
Strong background in data engineering, machine learning, and cloud-native architectures, with expertise in building scalable AI systems for enterprise environments.
Design end-to-end AI/ML architectures using Azure Databricks, AgentBricks, and Azure AI services.
Define best practices for integrating LLM-based agents, data pipelines, and orchestration frameworks.
Architect and optimize ETL pipelines for large-scale data ingestion and transformation.
Implement feature engineering, model training, and deployment workflows in Databricks.
Build and deploy AgentBricks-based AI agents for automation, decision-making, and conversational interfaces.
Integrate agents with enterprise systems and APIs for real-time operations.
Ensure compliance with data governance, security, and responsible AI principles.
Work closely with data scientists, ML engineers, and business stakeholders to align AI solutions with strategic goals.
Required Skills
Strong experience with Azure Databricks (Spark, Delta Lake, MLflow).
Well versed with MCP concepts and Orchestration of agents at enterprise level.
Hands‑on experience with AgentBricks for building agentic workflows.
Proficiency in Python, SQL, and distributed computing frameworks.
Deep understanding of LLMs, prompt engineering, and agent orchestration.
Familiarity with Azure AI services (OpenAI).
Solid knowledge of Azure ecosystem, including Data Lake, Synapse, Event Hub, and Key Vault.
Strong communication and stakeholder management skills.
Ability to lead technical discussions and mentor teams.
Seniority Level Mid‑Senior level
Employment Type Full‑time
Job Function Information Technology
Industries IT Services and IT Consulting
Benefits
Medical insurance
401(k)
Vision insurance
#J-18808-Ljbffr
AI Architect
Location:
Grand Rapids, MI - Hybrid
Role Overview
Strong background in data engineering, machine learning, and cloud-native architectures, with expertise in building scalable AI systems for enterprise environments.
Design end-to-end AI/ML architectures using Azure Databricks, AgentBricks, and Azure AI services.
Define best practices for integrating LLM-based agents, data pipelines, and orchestration frameworks.
Architect and optimize ETL pipelines for large-scale data ingestion and transformation.
Implement feature engineering, model training, and deployment workflows in Databricks.
Build and deploy AgentBricks-based AI agents for automation, decision-making, and conversational interfaces.
Integrate agents with enterprise systems and APIs for real-time operations.
Ensure compliance with data governance, security, and responsible AI principles.
Work closely with data scientists, ML engineers, and business stakeholders to align AI solutions with strategic goals.
Required Skills
Strong experience with Azure Databricks (Spark, Delta Lake, MLflow).
Well versed with MCP concepts and Orchestration of agents at enterprise level.
Hands‑on experience with AgentBricks for building agentic workflows.
Proficiency in Python, SQL, and distributed computing frameworks.
Deep understanding of LLMs, prompt engineering, and agent orchestration.
Familiarity with Azure AI services (OpenAI).
Solid knowledge of Azure ecosystem, including Data Lake, Synapse, Event Hub, and Key Vault.
Strong communication and stakeholder management skills.
Ability to lead technical discussions and mentor teams.
Seniority Level Mid‑Senior level
Employment Type Full‑time
Job Function Information Technology
Industries IT Services and IT Consulting
Benefits
Medical insurance
401(k)
Vision insurance
#J-18808-Ljbffr