Gen. AI Engineer

Kaleidoscope Innovation; Fort Worth (TX); On-site; USD 140,000 - 190,000; Full time

Job summary

Kaleidoscope Innovation seeks a Senior GenAI/Agentic AI Engineer to design, build, and deploy enterprise-scale AI applications using LLMs, RAG, and multi-agent architectures. You will craft scalable pipelines, AI agents, and secure APIs for production environments.

The role emphasizes hands-on development across cloud-native stacks (AWS/Azure/GCP), containerization (Docker/Kubernetes), and IaC, driving observability and governance for responsible AI practices.

Qualifications

• 8+ years of software engineering, cloud engineering, AI/ML, or platform engineering experience.
• 3+ years of hands-on experience building production Generative AI or LLM-based applications.
• Strong expertise with Python and API development using FastAPI, Flask, or similar frameworks.
• Experience with RAG solutions and vector databases (e.g., Pinecone, Weaviate, Chroma, Milvus, Azure AI Search).
• Experience with Agentic AI frameworks (LangChain, LangGraph, CrewAI, LlamaIndex, Semantic Kernel, AutoGen).
• Strong understanding of prompt engineering, tool calling, agent orchestration, and workflow automation.

Responsibilities

• Design and develop enterprise Generative AI applications using LLMs, RAG, Graph RAG, and multi-agent architectures.
• Build scalable document ingestion, embedding, retrieval, and vector search pipelines.
• Develop AI agents using LangChain, LangGraph, CrewAI, LlamaIndex, AutoGen, or similar.
• Create secure backend services and APIs using Python, FastAPI, Flask.
• Build AI-powered web applications using React, Angular, or Next.js.
• Deploy cloud-native AI solutions across AWS, Azure, and GCP using Docker, Kubernetes, and IaC.
• Implement observability, monitoring, LLMOps, and governance for production reliability.

Skills

Python

API development

LLM integration

Docker/Kubernetes

Cloud platforms

LangChain/LangGraph

Tools

Pinecone

Weaviate

Chroma

Milvus

Azure AI Search

LangChain

LangGraph

CrewAI

LlamaIndex

AutoGen

Job description

Overview

We are seeking a Senior GenAI / Agentic AI Engineer to design, build, and deploy enterprise-scale AI applications that leverage Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Agentic AI, and cloud-native technologies. This is a hands-on engineering role focused on building production-ready AI platforms from architecture through deployment.

Overview

We are seeking a Senior GenAI / Agentic AI Engineer to design, build, and deploy enterprise-scale AI applications that leverage Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Agentic AI, and cloud-native technologies. This is a hands-on engineering role focused on building production-ready AI platforms from architecture through deployment.

The ideal candidate has extensive experience developing scalable AI solutions, integrating LLMs into enterprise applications, and delivering secure, reliable systems that operate in production environments.

Responsibilities

• Design and develop enterprise Generative AI applications using LLMs, RAG, Graph RAG, and multi-agent architectures.
• Build scalable document ingestion, embedding, retrieval, and vector search pipelines.
• Develop AI agents using frameworks such as LangChain, LangGraph, CrewAI, LlamaIndex, AutoGen, or similar technologies.
• Create secure backend services and APIs using Python, FastAPI, Flask, or comparable frameworks.
• Build intuitive AI-powered web applications using modern front-end technologies such as React, Angular, or Next.js.
• Deploy cloud-native AI solutions across AWS, Azure, and GCP using Docker, Kubernetes, and Infrastructure-as-Code.
• Implement observability, monitoring, LLMOps, and governance to ensure production reliability and responsible AI practices.
• Collaborate with product, engineering, architecture, and business stakeholders to deliver enterprise AI solutions.
  
  

Required Qualifications

• 8+ years of software engineering, cloud engineering, AI/ML, or platform engineering experience.
• 3+ years of hands-on experience building production Generative AI or LLM-based applications.
• Strong expertise with Python and API development using FastAPI, Flask, or similar frameworks.
• Experience building Retrieval-Augmented Generation (RAG) solutions and working with vector databases such as Pinecone, Weaviate, Chroma, Milvus, or Azure AI Search.
• Experience with Agentic AI frameworks including LangChain, LangGraph, CrewAI, LlamaIndex, Semantic Kernel, or AutoGen.
• Strong understanding of prompt engineering, tool calling, agent orchestration, and workflow automation.
• Experience developing cloud-native applications on AWS, Azure, or GCP.
• Hands-on experience with Docker, Kubernetes, Terraform, CI/CD pipelines, and modern DevOps practices.
• Experience integrating enterprise AI applications with databases, APIs, and business systems.
• Strong understanding of security, governance, and responsible AI best practices.
  
  

Preferred Qualifications

• Experience implementing Graph RAG and knowledge graph solutions.
• Experience with MCP (Model Context Protocol) architecture.
• Experience deploying models using vLLM, Hugging Face, Triton, or TensorRT-LLM.
• Experience with Databricks, Spark, Kafka, Snowflake, or modern data engineering platforms.
• Experience building AI applications within regulated industries such as Financial Services, Healthcare, or Insurance.
• Azure, AWS, Google Cloud, or Databricks AI certifications.
  
  

Technical Environment

• Languages: Python, JavaScript/TypeScript, SQL
• Frameworks: LangChain, LangGraph, CrewAI, LlamaIndex, FastAPI, Flask, React, Angular, Next.js
• Cloud: AWS, Azure, GCP
• Vector Databases: Pinecone, Weaviate, Chroma, Milvus, Azure AI Search
• DevOps: Docker, Kubernetes, Terraform, GitHub Actions, Jenkins
• AI Platforms: OpenAI, Claude, Gemini, Llama, AWS Bedrock, Azure OpenAI