AI/ML Engineer

eTeam Inc
New York, NY, United States
3 days ago
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Role details

Contract type
Temporary contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
10 years minimum
Working hours
Regular working hours

Tech stack

LangGraph Framework Application Programming Interfaces (APIs) Artificial Intelligence Microsoft Azure Databases Data Governance Data Systems Memory Management Python (Programming Language) Systems Development Life Cycle SQL Databases Enterprise Software Applications
+15 more
LangChain Retrieval-Augmented Generation Snowflake Multi-Agent Systems Prompt Engineering Apache Spark Generative AI AI Coding Agents Agentic-AI Event Driven Architecture Containerization Pyspark Data Management Semantic Kernel Databricks

Job description

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.

Requirements

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

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