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Calling Agent Jobs (NOW HIRING)

Diamondback E&P LLC

AI Developer

Dallas, TX · On-site

Familiarity with the Model Context Protocol (MCP) or other tool-calling / agent orchestration patterns * Experience with infrastructure-as-code, containerization, or cloud deployment practices

Diamondback Energy, Inc.

AI Developer

Dallas, TX · On-site

Familiarity with the Model Context Protocol (MCP) or other tool-calling / agent orchestration patterns * Experience with infrastructure-as-code, containerization, or cloud deployment practices

Diamondbackenergy

AI Developer

Dallas, TX

Familiarity with the Model Context Protocol (MCP) or other tool-calling / agent orchestration patterns * Experience with infrastructure-as-code, containerization, or cloud deployment practices

Diamondback Energy, Inc.

Familiarity with the Model Context Protocol (MCP) or other tool-calling / agent orchestration patterns * Experience with infrastructure-as-code, containerization, or cloud deployment practices

INFOSYS NOVA HOLDINGS LLC

Gen. AI Engineer

Fort Worth, TX · On-site

$100K - $160K/yr

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 ...

Valsoft Corporation

Variphy Colleen, AI Calling Agent. An AI agent that augments call queues and hunt groups. * Flexible deployment. On-premises or Variphy Cloud, so customers aren't locked into a delivery model. Your ...

Dentsu, Inc.

Associate Director, AI Engineer

New York, NY · On-site

$94K - $152K/yr

... calling, agent frameworks). * Experience with at least one agent orchestration framework (LangChain, LangGraph, AutoGen, CrewAI, or similar). * Strong system design skills, including API architecture ...

Oracle

Consulting Member of Technical Staff

Austin, TX · On-site

... calling, agent frameworks, harnesses, evaluations, guardrails, or workflow automation. • Strong security judgment, communication skills, and technical leadership across secure coding, dependency ...

Brillio

Principal Architect - CPQ product

Dallas, TX · On-site

Core LLM engineering: designing agentic systems with frontier models (Claude / GPT) - tool / function calling, agent skills, multi-step orchestration, and memory. * Production RAG: embeddings, vector ...

Brillio

Principal Architect - CPQ product

Dallas, TX

Core LLM engineering: designing agentic systems with frontier models (Claude / GPT) - tool / function calling, agent skills, multi-step orchestration, and memory. * Production RAG: embeddings, vector ...

Amdocs

Software Engineer - Graduate

Plano, TX · On-site

Experience designing and integrating Tool-calling / agent skills (function calling, tool interfaces, input/output schemas, guardrails, structured outputs) into data pipelines or services * APIs ...

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Showing results 41-60

All JobsBusiness JobsCustomer Service JobsCall Center Representative JobsCalling Agent Jobs

Calling Agent information

What is the difference between Calling Agent vs Customer Service Representative?

AspectCalling AgentCustomer Service Representative
Required CredentialsHigh school diploma; communication skillsHigh school diploma; communication skills
Work EnvironmentCall centers, telecommunication companiesCall centers, retail, service industries
Employer & Industry UsageTelecom, sales, lead generationRetail, banking, tech support
Search & Comparison IntentFocus on outbound calling, sales, or lead generationFocus on customer support, issue resolution

Calling Agents primarily focus on outbound calls for sales or lead generation, while Customer Service Representatives handle inbound calls to assist customers with issues or inquiries. Both roles require strong communication skills and often work in call centers, but their main objectives differ: sales versus support.

How to become a calling agent?

To become a calling agent, typically you need a high school diploma or equivalent, strong communication skills, and the ability to handle customer interactions. Some employers may require experience with customer service or sales, and proficiency with call center software or CRM tools can be beneficial. Training is often provided on the job to familiarize new agents with company protocols and scripts.
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Calling Agent jobs near you
Infographic showing various Calling Agent job openings in the United States as of August 2026, with employment types broken down into 93% Full Time, 6% Part Time, and 1% Contract. Highlights an 37% Physical, and 63% Remote job distribution.

Gen. AI Engineer

Fort Worth, TX • On-site

Kaleidoscope Innovation, Inc.
51 - 200 employees
Learn more about Kaleidoscope Innovation, Inc.external

$100K - $160K/yr

Other

Posted 25 days ago

Key responsibilities

  • Design, develop, and deploy enterprise-scale Generative AI applications leveraging LLMs, RAG, and multi-agent architectures.

  • Build scalable document ingestion, embedding, retrieval, and vector search pipelines, and develop AI agents using frameworks such as LangChain, LangGraph, CrewAI, LlamaIndex, or AutoGen.

  • Create secure backend services and APIs, and build AI-powered web applications using modern front-end technologies, deploying solutions across cloud platforms with containerization and infrastructure automation.

Job description

If you are unable to complete this application due to a disability, contact this employer to ask for an accommodation or an alternative application process.

Fort Worth, TX, US

5 days ago Requisition ID: 1274

Salary Range: $100,000.00 To $160,000.00 Annually

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.
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