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Generative Ai Chatbot Jobs in Washington (NOW HIRING)

Freddie Mac

Senior Director, Software Engineering

Mclean, VA · On-site

$255K/yr

Freddie Mac is seeking a Sr. Director, Generative AI Development to lead a team of engineers building and operating internal Generative AI capabilities, including the company's internal chatbot and ...

Freddie Mac

Senior Director, Software Engineering

Mclean, VA · On-site

$255K/yr

Freddie Mac is seeking a Sr. Director, Generative AI Development to lead a team of engineers building and operating internal Generative AI capabilities, including the company's internal chatbot and ...

Node.Digital

Senior AI/ML Engineer

Herndon, VA · On-site

$107K - $147K/yr

Experience with generative AI models and frameworks (LLMs, RAG architectures, prompt engineering ... chatbot development and conversational AI Experience with AWS Bedrock Agents and Guardrails ...

Node.Digital

Senior AI/ML Engineer

Herndon, VA · On-site +1

$107K - $147K/yr

Experience with generative AI models and frameworks (LLMs, RAG architectures, prompt engineering ... chatbot development and conversational AI Experience with AWS Bedrock Agents and Guardrails ...

Node.Digital LLC

Senior AI/ML Engineer

Herndon, VA · On-site

$140 - $190/hr

Experience with generative AI models and frameworks (LLMs, RAG architectures, prompt engineering ... Knowledge of chatbot development and conversational AI * Experience with AWS Bedrock Agents and ...

Node.Digital

Senior AI/ML Engineer

Herndon, VA · On-site

$107K - $147K/yr

Experience with generative AI models and frameworks (LLMs, RAG architectures, prompt engineering ... chatbot development and conversational AI Experience with AWS Bedrock Agents and Guardrails ...

Gartner

Director, Data Science

Arlington, VA · Remote

Large Language Models/Generative AI, conversational AI/chatbot development, NLP/text mining, search & recommendation systems, prompt engineering/LLM optimization, AI agent architectures.

Gartner

Director, Data Science

Arlington, VA · On-site

Large Language Models/Generative AI, conversational AI/chatbot development, NLP/text mining, search & recommendation systems, prompt engineering/LLM optimization, AI agent architectures.

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Generative Ai Chatbot information

What is the difference between Generative Ai Chatbot vs Data Scientist?

AspectGenerative Ai ChatbotData Scientist
Required CredentialsBasic programming, AI/ML knowledgeDegree in Data Science, Statistics, or related field
Work EnvironmentTech companies, customer service platformsResearch labs, corporate analytics teams
Industry UsageAutomated customer interactions, content generationData analysis, predictive modeling, insights
Search & Comparison IntentUnderstanding AI chatbot capabilitiesData analysis skills and roles

Generative Ai Chatbots focus on creating conversational AI for customer engagement, requiring programming and AI knowledge. Data Scientists analyze data to generate insights, often with advanced degrees. While both work in tech environments, their roles differ in purpose and skill set.

What are some common challenges faced by professionals working on generative AI chatbot development, and how can they be addressed?

Professionals developing generative AI chatbots often encounter challenges such as managing ambiguous user inputs, ensuring conversational relevance, and maintaining ethical standards like avoiding biased or inappropriate responses. Collaboration with interdisciplinary teams—including data scientists, linguists, and UX designers—is vital to continuously improve the chatbot's performance. Regular testing, user feedback, and fine-tuning of language models are essential practices to address these challenges and enhance the chatbot's ability to handle diverse real-world conversations.

What are the key skills and qualifications needed to thrive as a generative AI chatbot developer, and why are they important?

To thrive as a Generative AI Chatbot Developer, you need strong programming expertise (especially in Python), a solid understanding of machine learning and natural language processing (NLP), and typically a degree in computer science or a related field. Familiarity with frameworks like TensorFlow or PyTorch, experience with APIs, and knowledge of cloud platforms such as AWS or Azure are commonly required, along with relevant AI or ML certifications. Creativity, problem-solving, and effective communication are vital soft skills for designing engaging, user-friendly conversational experiences and collaborating with cross-functional teams. These skills are crucial for building reliable, scalable, and innovative AI chatbots that meet user needs and business objectives.

What is a generative AI chatbot?

A Generative AI Chatbot is an artificial intelligence system designed to engage in human-like conversations by generating responses to user inputs in real time. Unlike traditional rule-based chatbots that rely on predefined scripts, generative AI chatbots use advanced machine learning models—often based on large language models—to understand context and produce original, relevant responses. These chatbots can be used in customer service, education, entertainment, and more, offering personalized and dynamic interactions. They continue to improve as they process more data and user interactions.
What are popular job titles related to Generative Ai Chatbot jobs in Washington? For Generative Ai Chatbot jobs in Washington, the most frequently searched job titles are:
What job categories do people searching Generative Ai Chatbot jobs in Washington look for? The top searched job categories for Generative Ai Chatbot jobs in Washington are:
What cities in Washington are hiring for Generative Ai Chatbot jobs? Cities in Washington with the most Generative Ai Chatbot job openings:
Generative Ai Chatbot jobs near you
Infographic showing various Generative Ai Chatbot job openings in Washington as of August 2026, with employment types broken down into 76% Full Time, 21% Part Time, and 3% Contract. Highlights an 67% Physical, 4% Hybrid, and 29% Remote job distribution.

Chatbot Developer - Conversational AI

Noblesoft Technologies

Adelphi, MD • Remote

Contractor

Re-posted yesterday

Job description

Role: Chatbot Developer - Conversational AI

Location: Remote (US) EST hours

Duration: 3 months

  

Role Overview
We are seeking a talented and passionate Conversational AI Developer to play a pivotal role in managing current day chatbot implantations and designing, building, and optimizing our next-generation conversational experiences. In this role, you will bridge the gap between classical NLU systems and modern Generative AI orchestrations. You will be responsible for maintaining our robust enterprise foundations while actively driving our migration strategy toward autonomous agent frameworks.
 
The ideal candidate possesses a deep technical background in the Microsoft conversational ecosystem, a strong understanding of enterprise integration layers, and a passion for delivering seamless, human-like, yet transparent user experiences.
 
Key Responsibilities
  • End-to-End Development: Drive the full lifecycle development (from conversational design to production deployment) of scalable chatbots, virtual assistants, and AI agents.
  • Architecture Migration: Maintain and optimize our current Azure Bot Framework SDK v4 stack while actively participating in the architectural migration toward Microsoft Foundry and Agents 365 Azure SDK.
  • Enterprise Integration: Design and implement robust API integrations using MuleSoft as the central enterprise service bus to orchestrate data exchange between conversational front ends and core backend systems, including PeopleSoft and Salesforce.
  • Omnichannel Dialog Management: Author and manage rich, dynamic conversational interfaces using Microsoft Dynamics Adaptive Cards, Knowledge Management systems, and Automation Flows across web, mobile, and messaging channels.
  • Live Chat and Case Management: Build seamless escalation protocols, including live agent handoffs to Salesforce Live Chat and automated ticket routing via Salesforce Case Management APIs.
  • NLU and LLM Orchestration: Integrate Hybrid AI strategies by combining classical NLU (Azure Conversational Language Understanding/CLU) with Large Language Models (Azure OpenAI/GPT) for intelligent intent routing, fallback handling, and contextual content generation.
  • Performance Optimization: Analyze conversation logs, containment rates, and intent accuracy metrics using data visualization tools to continuously optimize conversational flows and minimize hallucinations.
  • Cross-Functional Collaboration: Partner closely with Product Managers, UX Designers, and business stakeholders to translate complex business logic into intuitive user stories and turn technical constraints into delightful user experiences.
 
Technical & Professional Qualifications
Required Experience
  • 3+ years of dedicated experience in software development with a specialized focus on Conversational AI, NLP/NLU, or LLM agent development.
  • Microsoft Bot Stack Expertise: Deep, hands-on proficiency with Azure Bot Framework SDK v4 (including Waterfall Dialogs, custom middleware, and state management) alongside experience or strong theoretical knowledge of Copilot Studio / Agents 365.
  • Core Backend Skills: Strong programming fundamentals with advanced proficiency in C#, .NET, and JavaScript, combined with frontend capabilities (HTML/CSS) for custom web-chat styling and Adaptive Card rendering.
  • Enterprise Systems Integration: Direct experience working with MuleSoft layers to pull/push data from legacy enterprise platforms like PeopleSoft and CRM systems like Salesforce.
 
Preferred Qualifications
  • Data and State Management: Experience configuring and querying Azure Cosmos DB for storing conversation state, user context, and telemetry logs.
  • Analytics Driven: Familiarity utilizing Power BI or Azure Application Insights to analyze drop-off points, intent confusion matrices, and chatbot containment metrics.
  • Modern DevOps: Experience defining and maintaining CI/CD pipelines for conversational assets across Dev, Test, and Production environments.
  • Industry Context: Experience implementing conversational solutions within Higher Education or complex, multi-stakeholder enterprise environments is a plus.
  • Soft Skills: Exceptional communication skills with the ability to articulate technical AI constraints to non-technical business stakeholders.
 
Benefits & Culture
  • Cutting-Edge Innovation: Be part of a forward-thinking team actively reshaping the digital student and staff experience through advanced AI and Agentic workflows.
  • Impact-Driven Work: Build tools that directly solve user pain points, handling high-volume transactions with immediate real-world impact.
  • Professional Growth: Work in a fast-paced environment that actively supports upskilling in Generative AI, LLM orchestration, and next-generation Microsoft AI technologies.