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Dialogflow Jobs (NOW HIRING)

Cresta

Associate Conversational AI Designer

OR · On-site +1

$60K - $95K/yr

Design and develop virtual agent solutions using Google's Dialogflow CX. Qualifications We Value: * Strong communication skills (verbal and written). * Desire to work in a fast-paced environment with ...

Teklead Corp

Sr Chatbot Engineer

Westlake Village, CA · Hybrid

$68 - $78/hr

Compiler development experience is plus Experience with chat platforms Dialogflow, Connect-Q, etc is a plus Experience with Hybrid RAG Agents, Trainable LLMs is a plus BS in Computer Science or ...

United IT

Sr. Python Developer

Austin, TX · On-site

$120K - $162K/yr

Interface with APIs (e.g., OpenAI, Dialogflow, Rasa) for NLP and conversation flow. Maintain context and state across asynchronous message streams. 4. Real-Time Message Processing Work with Kafka or ...

United IT Solutions

Sr. Python Developer

Austin, TX · On-site

$120K - $162K/yr

Interface with APIs (e.g., OpenAI, Dialogflow, Rasa) for NLP and conversation flow. Maintain context and state across asynchronous message streams. 4. Real-Time Message Processing Work with Kafka or ...

Apex Informatics

Java AI Developer - Backend AI

Phoenix, AZ · On-site

$50.25 - $65/hr

Dialogflow CX or similar platforms * LLMs and prompt engineering concepts * Agentic frameworks (ADK or similar) Nice to Have * Experience in banking, fintech, or digital platforms * Familiarity with ...

Axos Bank

Conversational AI Engineer

San Diego, CA · On-site

$70K - $93K/yr

This role works primarily within the Google CCAS suite, including Dialogflow Conversational Agents, and GCP, and plays a critical role in both production support and platform enhancements. The ...

UrBench

Solution Architect

Chicago, IL · On-site

$65 - $85.50/hr

Hands-on experience with NLP/NLU tools (e.g., Amazon Lex, Google Dialogflow, Rasa, Azure Bot Framework) * Exposure to Retrieval-Augmented Generation (RAG) models for dynamic, context-aware responsesa

Axos Bank

Conversational AI Engineer

San Diego, CA

$70K - $93K/yr

This role works primarily within the Google CCAS suite, including Dialogflow Conversational Agents, and GCP, and plays a critical role in both production support and platform enhancements. The ...

Omega Solutions Inc

Chatbot Developer with Azure

Dallas, TX · On-site

$54.75 - $67.75/hr

Nice to have skills • Experience in working with any AI/NLP platform (DialogFlow/ Alexa/ Converse.ai/ Amazon Lex etc.) for building chatbots Experience with any one of the technology (JavaScript ...

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$19

$65

$91

How much do dialogflow jobs pay per hour?

As of Jul 5, 2026, the average hourly pay for dialogflow in the United States is $65.93, according to ZipRecruiter salary data. Most workers in this role earn between $58.89 and $84.13 per hour, depending on experience, location, and employer.

What is a Dialogflow job?

A Dialogflow job typically involves designing, building, and optimizing conversational AI solutions using Google Dialogflow. Responsibilities may include creating intelligent chatbots, integrating natural language processing (NLP) models, and improving user interactions. Professionals in this field often work as chatbot developers, AI engineers, or conversational UX designers. Strong knowledge of machine learning, APIs, and cloud platforms is beneficial for this role.

What are the key skills and qualifications needed to thrive in the Dialogflow position, and why are they important?

To succeed as a Dialogflow Developer or Specialist, you need expertise in conversational AI design, strong programming skills (especially in JavaScript or Python), and experience with Natural Language Processing (NLP) frameworks. Familiarity with Google Cloud Platform, Dialogflow CX/ES, API integration, and relevant certifications such as Google Cloud Dialogflow certification are highly valuable. Excellent problem-solving abilities, communication skills, and attention to user experience will set you apart. These competencies are crucial for delivering robust, user-friendly chatbot solutions that align with client requirements and business goals.

What are the typical responsibilities of a Dialogflow Developer in a workday?

A Dialogflow Developer typically spends their day designing, building, and maintaining conversational agents and chatbots using Dialogflow. This includes creating intents and entities, integrating APIs, testing natural language models, and collaborating with UX designers and other engineers to enhance conversation flows. You may also be tasked with troubleshooting user issues, analyzing performance metrics, and optimizing chatbot performance based on user feedback. The role often requires teamwork across product, development, and customer support departments to ensure seamless virtual assistant solutions that meet business objectives.

More about Dialogflow jobs
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Dialogflow jobs near you
Infographic showing various Dialogflow job openings in the United States as of June 2026, with employment types broken down into 89% Full Time, and 11% Contract. Highlights an 63% Physical, 11% Hybrid, and 26% Remote job distribution, with an average salary of $137,142 per year, or $65.9 per hour.
Senior AI Architect & Lead Prompt Engineer

Senior AI Architect & Lead Prompt Engineer

Connect Tech+Talent

Sunnyvale, CA • On-site

Other

Posted 3 days ago

Job description

Job Description Senior AI Architect & Lead Prompt Engineer Location: Sunnyvale, CA Contract Role Overview The Senior AI Architect & Lead Prompt Engineer will spearhead the design and deployment of advanced, next-generation agentic systems and LLM-powered platforms for GFiber. This pivotal role necessitates the integration of sophisticated Prompt Engineering and AI Architecture principles with scalable AI infrastructure to optimize GFiber's enterprise workflows. Leveraging a background in the Telecommunications sector, the incumbent will integrate AI agents with core enterprise platforms, including but not limited to ServiceNow, Salesforce, Netcracker, and SAP, to automate complex customer inquiry cycles and enhance on-field employee support.

This integration is designed to yield substantial reductions in Capex and Opex, ensure end-to-end service management for both internal and external GFiber stakeholders, and involve the creation of reusable AI assets and the cultivation of mentorship capabilities. Key Responsibilities AI Architecture & Design: Lead the end-to-end architecture of multi-agent systems, moving from initial concept to production-grade deployment on Google Cloud Platform (GCP). Prompt Engineering & Orchestration: Develop sophisticated prompt engineering frameworks, including system prompts, few-shot templates, and output guardrails.

Utilize Chain-of-Thought (CoT) prompting and structured prompt chains for complex reasoning tasks. Intelligent Dialog Systems: Design conversational interfaces using Dialogflow and Gemini-powered agents to manage inquiry routing and automated workflow orchestration. System Integration: Architect integrations between LLM platforms (Vertex AI/Gemini) and enterprise CRM/ITSM tools like Salesforce and ServiceNow, specifically focusing on Telecom-grade inquiry response and ticketing workflows.

RAG & Knowledge Retrieval: Build and optimize RAG (Retrieval-Augmented Generation) pipelines grounded in internal client policies and technical documentation. MLOps & Deployment: Oversee the deployment of microservices using GKE (Google Kubernetes Engine), Cloud SQL, and Cloud Build, ensuring scalable and reliable AI performance. Required Core Expertise LLM Stack: Deep expertise in Gemini, Vertex AI, and LangChain or LlamaIndex.

Enterprise Integration: Proven experience architecting AI solutions that interface with Salesforce and ServiceNow within a Telecom or large enterprise context. Agentic Systems: Experience building multi-agent architectures for autonomous task execution and workflow automation. Data & Search: Mastery of hybrid search, reranking, and vector databases (e.g., Redis, PostgreSQL)

Qualifications Experience: 10+ years in the AI stack, ranging from classical NLP/NLU to modern generative AI architectures. Education: B.Tech in Computer Science, Mathematics, or a related technical field. Technical Proficiency: Strong command of Python, Terraform IAC, Docker, and the GCP ecosystem (GKE, Cloud Deploy)

Industry Knowledge: Demonstrated understanding of the Service Now, Salesforce, Net Cracker in Telecommunications service lifecycle, specifically regarding inquiry management and automated support. Tools & Platforms AI/ML: Gemini, Vertex AI, Hugging Face, OpenAI, Claude. Frameworks: LangChain, LlamaIndex, Dialogflow.

Cloud & Infra: GCP (GKE, Cloud Build), Docker, TensorRT. Data: Cloud SQL, PostgreSQL, Redis.

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