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AIML Engineer
Job Location:
Job Location:
New York City, NY - USA
Monthly Salary:
Not provided by the employer
Monthly Salary:
Posted:
25 October 2026 (7 hours ago)
Posted:
Application Deadline:
22 January 2027
Application Deadline:
Vacancies:
1 Vacancy
Vacancies:
Job Summary
Job Title: AI/ML Engineer
Location: New York NY 10004 (Hybrid)
Duration: 12 Months
Job Details:
Must Have Skills
Gen AI AI/ML RAG LangChain Python Spark Snowflake
Nice to have skills
Azure
Detailed Job Description
Design and develop scalable AI-powered data platforms and agentic AI solutions that enable autonomous decision-making intelligent workflow orchestration and business process automation.
Build and maintain data engineering pipelines using Python Spark Databricks Snowflake SQL and cloud-native technologies to support AI/ML GenAI and analytics workloads.
Architect and implement multi-agent AI systems with capabilities such as goal decomposition task planning reasoning memory management self-reflection tool utilization and autonomous execution.
Develop and optimize Retrieval-Augmented Generation (RAG) solutions including document ingestion chunking embedding generation vector database integration retrieval optimization and response grounding.
Integrate AI agents with enterprise systems APIs databases knowledge repositories CI/CD pipelines and event-driven architectures to create end-to-end intelligent automation frameworks.
Design and implement data governance security guardrails monitoring and compliance controls to ensure responsible AI adoption and protection of enterprise data assets.
Build reusable AI engineering components using modern frameworks such as LangChain LangGraph Semantic Kernel ClientP-based architectures and agent orchestration platforms.
Evaluate and improve AI system performance through prompt engineering agent testing frameworks model benchmarking retrieval accuracy analysis latency optimization and continuous feedback loops.
Collaborate with architects data scientists application teams and business stakeholders to translate complex business requirements into scalable AI-driven data solutions and production-ready platforms.
Provide technical leadership and mentorship by driving AI engineering best practices conducting architecture reviews developing reusable accelerators and enabling engineering teams to leverage AI-assisted software development and agentic SDLC methodologies.
Skills:
Python PySpark SQL Databricks Snowflake
GenAI Agentic AI ClientP Architecture RAG
LangChain LangGraph Semantic Kernel
Minimum years of experience
>10 years
Top 3 responsibilities:
Coding
Testing
Deployment
Location: New York NY 10004 (Hybrid)
Duration: 12 Months
Job Details:
Must Have Skills
Gen AI AI/ML RAG LangChain Python Spark Snowflake
Nice to have skills
Azure
Detailed Job Description
Design and develop scalable AI-powered data platforms and agentic AI solutions that enable autonomous decision-making intelligent workflow orchestration and business process automation.
Build and maintain data engineering pipelines using Python Spark Databricks Snowflake SQL and cloud-native technologies to support AI/ML GenAI and analytics workloads.
Architect and implement multi-agent AI systems with capabilities such as goal decomposition task planning reasoning memory management self-reflection tool utilization and autonomous execution.
Develop and optimize Retrieval-Augmented Generation (RAG) solutions including document ingestion chunking embedding generation vector database integration retrieval optimization and response grounding.
Integrate AI agents with enterprise systems APIs databases knowledge repositories CI/CD pipelines and event-driven architectures to create end-to-end intelligent automation frameworks.
Design and implement data governance security guardrails monitoring and compliance controls to ensure responsible AI adoption and protection of enterprise data assets.
Build reusable AI engineering components using modern frameworks such as LangChain LangGraph Semantic Kernel ClientP-based architectures and agent orchestration platforms.
Evaluate and improve AI system performance through prompt engineering agent testing frameworks model benchmarking retrieval accuracy analysis latency optimization and continuous feedback loops.
Collaborate with architects data scientists application teams and business stakeholders to translate complex business requirements into scalable AI-driven data solutions and production-ready platforms.
Provide technical leadership and mentorship by driving AI engineering best practices conducting architecture reviews developing reusable accelerators and enabling engineering teams to leverage AI-assisted software development and agentic SDLC methodologies.
Skills:
Python PySpark SQL Databricks Snowflake
GenAI Agentic AI ClientP Architecture RAG
LangChain LangGraph Semantic Kernel
Minimum years of experience
>10 years
Top 3 responsibilities:
Coding
Testing
Deployment
Required Experience:
IC
