AI Engineer (GenAI) Mid level - 100% Remote - Zensoft IT Solutions - Remote | Dice.com

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AI Engineer (GenAI) Mid level - 100% Remote

Remote • Posted 4 hours ago • Updated 4 hours ago

Contract Independent

Contract W2

No Travel Required

Able to Sponsor

Remote

$70+

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Zensoft IT Solutions

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Job Details

Skills

python
RAG
Azure OpenAI
Databricks

Summary

JOB TITLE: Mid level Gen AI Engineer.

One of our hospitality and gaming customer based out of Las Vegas, NV is looking for a Generative AI Engineer to drive the development of cutting-edge AI applications, including RAG-based and agentic systems that process data from structured, unstructured sources, images, and PDFs.

Key Responsibilities

Design and implement RAG pipelines end-to-end, including document ingestion, chunking, embedding, retrieval, and response generation for well-scoped product features or internal tools.
Build and maintain LangGraph-based agents, modeling workflows as graphs (nodes, edges, conditional branches, loops) and integrating tools, retrievers, and external APIs.
Implement and operate MCP servers that expose tools/resources to LLM hosts, including request/response handling, basic error handling, and logging.
Integrate with LLM providers (e.g., Azure OpenAI, Databricks) and manage prompts, model configurations, and context windows for RAG-style interactions.
Work with vector stores (e.g., Azure AI Search) to set up indexes, tune similarity search, and manage metadata for retrieval.
Contribute to data ingestion pipelines for RAG (file connectors, text extraction, cleaning, metadata enrichment) in collaboration with data/platform teams.
Build and productionize GenAI and RAG-style workloads on Databricks, leveraging tools such as Databricks Genie / AI Assistant for SQL, notebooks, and pipeline development, and integrating Databricks-native vector search or ML flows where appropriate.
Design and implement AI-powered analytics and applications on Snowflake, using Snowflake Cortex capabilities (built-in LLM functions, embeddings, and vector search) as part of RAG and agent architectures.
Add observability to agents, RAG components, and MCP servers (logging, tracing, metrics), and use these to debug failures, latency issues, and incorrect tool usage.
Collaborate with product managers and senior engineers to translate requirements into technical designs and incremental delivery plans.
Participate in code reviews, testing, and documentation, improving reliability, maintainability, and clarity of RAG, LangGraph, Databricks, and Snowflake-related codebases.
Support security and compliance efforts by following established best practices around authentication, authorization, secrets management, and safe tool usage across cloud platforms.

Required Qualifications & Skills

5+ years of professional software engineering experience, with strong proficiency in Python (typing, packaging, testing, logging, async IO, REST APIs using frameworks like FastAPI/Flask).
Hands-on experience building at least one RAG-style application or search/QA system that uses embeddings and retrieval over private or domain-specific data.
Practical experience with vector databases or similarity search libraries, including index creation and query tuning.
Experience with LangChain (or similar orchestration frameworks) and working knowledge of LangGraph concepts such as state, nodes, edges, and graph-based flows.
Demonstrated ability to build and maintain agents that call external tools/APIs, handle multi-step reasoning, and manage conversation or workflow state.
Familiarity with Model Context Protocol (MCP) concepts and at least some hands-on work with implementing or integrating an MCP server or similar tool-bridge.
Solid understanding of prompting for RAG, including how to insert retrieved context, structure system/user prompts, and reduce hallucinations and irrelevant answers.
Experience with containerization and deployment (Docker; basic Kubernetes or equivalent is a plus) and CI/CD workflows for backend or ML/AI services.
Strong debugging and observability mindset, comfortable using logs, traces, and metrics dashboards to diagnose issues in distributed or tool-heavy workflows.
Good communication and documentation skills, comfortable explaining design choices and trade-offs to engineers, data scientists, and non-technical stakeholders.

Nice-to-Have (Plus)

Exposure to security considerations for LLM systems (prompt injection, data leakage, safe tool design) and working with security/compliance teams.
Deeper experience with Databricks ML/AI features (e.g., MLflow, Model Serving) or advanced Snowflake Cortex use cases (e.g., agent-style workflows or in-DB vector search at scale).
Experience contributing to architecture discussions and mentoring junior engineers on AI/LLM topics.

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.

Dice Id: RTX1c5908
Position Id: 55784
Posted 4 hours ago

Company Info

About Zensoft IT Solutions

Zensoft IT is a global service provider of Software Development, Process outsourcing, Corporate Consulting firm that is ready to meet every need of your Small, Medium & Large scale Businesses & Government Agencies let it be Manufacturing, Banking & Finance, Education, Insurance, Medical & Health Care, Multimedia & Entertainment, Real Estate, Retail Stores, Travel & Hospitality
We’re here to offer quality services in all aspects of Business Consulting, Resource Management (Staffing, Workforce Management, IT Consulting, Outsourcing), Project Management, Application Development and lot more.
We focus exclusively on maximizing client returns from outsourcing and off-shoring. We have extensive experience in managing large IT applications in real time as well as in providing high value services around packaged enterprise applications.

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AI Engineer (GenAI) Mid level - 100% Remote

Zensoft IT Solutions

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