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Agentic AI Engineer

TECHNEPTUNE CONSULTING INCNew York, NY🇺🇸United StatesPosted Oct 20, 2026

Quick Overview

Salary
$130k/yr
Seniority
Mid Senior
Work mode
Hybrid
Location
New York, NY, United States
Posted
21 hours ago
SQLETLSnowflakeDatabricksHadoopLangChainLangGraph

Job Description

Job Title: Agentic AI Engineer

Job Location: NYC, NY (Hybrid)

Job Type: FTE

Salary : $130K + Benefits

 

Need 7+ years of experience candidates for this role

 

Mandatory Skills- ETL, Snowflake, Data migration, Agentic AI, Cortex, LangGraph, LangChain, Hadoop, Databricks

 

Role Overview

We are seeking a highly skilled Agentic AI Engineer with expertise in Agentic AI, MCP (Model Context Protocol), Cortex, Evals, LangGraph, LangChain, Data Engineering, and Cloud Analytics Platforms. The ideal candidate will be responsible for designing, developing, and deploying enterprise-scale AI solutions, data modernization initiatives, and advanced analytics platforms that drive business transformation.

 

Key Responsibilities

AI & Agentic Systems

•             Design and develop Agentic AI applications leveraging LLMs and autonomous workflows.

•             Implement and manage Model Context Protocol (MCP) integrations for AI agent orchestration.

•             Build and optimize AI workflows using LangGraph and LangChain frameworks.

•             Develop AI evaluation frameworks using Evals to measure model performance, accuracy, and reliability.

•             Integrate enterprise knowledge sources and external tools into AI-powered solutions.

•             Work with Cortex AI platforms for model deployment, monitoring, and governance.

 

Data Engineering & Modernization

•             Design and implement scalable ETL/ELT pipelines for structured and unstructured data.

•             Lead data migration initiatives from legacy platforms to modern cloud ecosystems.

•             Build and optimize enterprise data lakes and data warehouses.

•             Develop data processing solutions using Hadoop, Databricks, and distributed computing frameworks.

•             Ensure data quality, governance, security, and compliance standards.

 

Cloud Data Platforms

•             Architect and manage data solutions on Snowflake and Databricks.

•             Optimize data storage, performance tuning, and cost management.

•             Develop complex SQL queries, stored procedures, and data transformation processes.

•             Integrate cloud-native analytics and AI capabilities with enterprise platforms.

 

Analytics & Visualization

•             Create interactive dashboards and executive reports using modern visualization tools.

•             Translate complex datasets into actionable business insights.

•             Work closely with stakeholders to define KPIs and reporting requirements.

 

 

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