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Conversational Ai Engineer Jobs in Rialto, CA (NOW HIRING)

Speechify

Go-to-Market - Anaheim, CA, USA

Anaheim, CA · On-site

$150K - $200K/yr

These include frontend and backend engineers, AI research scientists, and others from Amazon ... Experience selling AI, voice, or conversational technology * Familiarity with telephony ...

Yami

Senior Product Manager, Search and Discovery

Brea, CA · On-site

$100K - $135K/yr

... conversational/agentic shopping experiences (e.g., multi-turn dialogue, intent progression, AI ... Strong engineering and design judgment: able to partner with Engineering to make sound technical ...

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Conversational Ai Engineer information

See Rialto, CA salary details

$30.5K

$125.9K

$226.2K

How much do conversational ai engineer jobs pay per year?

As of Sep 3, 2026, the average yearly pay for conversational ai engineer in Rialto, CA is $125,855.00, according to ZipRecruiter salary data. Most workers in this role earn between $95,065.00 and $155,562.00 per year, depending on experience, location, and employer.

What is a conversational AI engineer?

A Conversational AI Engineer is a technology professional who designs, develops, and maintains systems that enable computers to interact with humans using natural language. They work on building chatbots, virtual assistants, and voice-enabled applications by leveraging natural language processing (NLP), machine learning, and AI frameworks. Their responsibilities include training language models, optimizing conversation flows, integrating with APIs, and ensuring the overall performance and accuracy of conversational systems. These engineers collaborate with data scientists, UX designers, and software developers to create seamless and intuitive AI-driven user experiences.

What are the key skills and qualifications needed to thrive as a conversational AI engineer?

To thrive as a Conversational AI Engineer, you need strong programming skills (such as Python), a background in natural language processing (NLP), and a degree in computer science or a related field. Familiarity with machine learning frameworks, chatbot platforms, and cloud services like AWS or Google Cloud is typically required, along with experience in tools such as TensorFlow or Rasa. Excellent problem-solving abilities, creativity, and clear communication help engineers design effective, user-friendly conversational systems. These skills ensure the development of robust, scalable, and intuitive AI solutions that meet user needs and business goals.

What are some common challenges conversational AI engineers face when deploying chatbots in production environments?

Conversational AI Engineers often encounter challenges such as ensuring chatbot robustness in handling diverse user inputs and maintaining natural, contextually relevant conversations. Managing scalability and latency is also crucial, as chatbots must perform efficiently under varying loads. Additionally, integrating with legacy systems and safeguarding user data privacy require careful coordination with DevOps and security teams. Continuous model monitoring and updating are essential to keep responses accurate and aligned with user expectations.

What is the difference between Conversational Ai Engineer vs Chatbot Developer?

AspectConversational Ai EngineerChatbot Developer
Required CredentialsBachelor's in CS, AI, or related field; experience with NLP and machine learningTypically programming skills; may have similar technical background
Work EnvironmentCollaborates on AI models, NLP, and user experience designFocuses on building and deploying chatbot interfaces
Employer & Industry UsageTech companies, AI startups, large enterprises integrating conversational AICustomer service, marketing, and sales sectors
Search & Comparison IntentUnderstanding roles in AI development, advanced conversational systemsBuilding specific chatbot applications

While both roles involve creating conversational interfaces, a Conversational Ai Engineer focuses on developing advanced AI models and NLP systems, whereas a Chatbot Developer primarily builds and deploys chatbot applications. The engineer's role is broader, often involving AI research and integration, while the developer concentrates on implementation and user interaction design.

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For Conversational Ai Engineer jobs in Rialto, CA, the most frequently searched job titles are:

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Cities near Rialto, CA with the most Conversational Ai Engineer job openings:

Conversational Ai Engineer jobs near you

Engineer in Residence: General Counsel (Mountain View)

AI Fund

Victorville, CA • On-site

$10K/mo

Full-time

Re-posted yesterday

Job description

Visiting Engineer: General Counsel

Mountain View, CA

AI Fund – AI Fund / Contract / On-site

What You’ll Build
  • A contract ingestion and parsing pipeline that handles PDFs, Word documents, and email attachments across varying formats and clause structures.
  • A clause extraction and classification system that identifies key terms, obligations, risk provisions, and non‑standard language with high precision.
  • A risk scoring engine that flags contracts or clauses that deviate from company‑approved templates or contain unusual terms.
  • A workflow layer that routes flagged items to the right reviewer with context, reducing the time from contract receipt to approval.
What You’ll Do
  • Design the document processing pipeline for handling the full diversity of enterprise contract formats.
  • Build extraction models that identify and classify contract clauses with precision high enough for legal teams to trust.
  • Develop a risk assessment framework that compares incoming contracts against company playbooks and approved clause libraries.
  • Implement a review workflow that integrates with existing legal tools (CLMs, matter management systems, email).
  • Work with in‑house legal design partners to validate accuracy and build trust in AI‑assisted contract review.
What You Need
  • Strong full‑stack or backend engineering skills. You have built and shipped production systems that process complex documents.
  • Experience with document processing, NLP, or information extraction from unstructured text.
  • Hands‑on experience building with LLMs, particularly for structured data extraction, classification, or reasoning tasks.
  • Ability to build systems where precision matters. Legal teams need to trust the output, so false positive management is critical.
  • Ability to work autonomously and make product and architecture decisions without waiting for direction.
Helpful But Not Required
  • Experience in legal tech, compliance tech, or regulated industry software.
  • Familiarity with contract lifecycle management (CLM) tools or legal workflow systems.
  • Background in document AI, OCR, or PDF processing pipelines.
  • Founder or founding engineer experience building for knowledge‑worker workflows.
Who This Is For

A builder who sees legal operations as a high‑value, underserved vertical for applied AI.
A person who understands that the hardest part is not extraction but precision: legal teams will not use a tool that makes mistakes on important clauses.

What To Know Upfront

This is a 12‑week, full‑time, on‑site residency in Mountain View, California.
Not every residency becomes a company. The goal is to pressure‑test the idea quickly and honestly with real users and customers.
You will be building an AI Fund idea, not bringing your own startup idea into the program.
The process typically includes a Builder Event or equivalent working conversation, then a 48‑hour Builder Challenge, then panel review with AI Fund build leadership.
The compensation is intentionally modest during the residency because the upside, if the idea works, is a founder‑level role.

Compensation
  • $10,000/month for 12 weeks ($30,000 total).
  • This is a contract role during the residency. If the build leads to a funded company, the next step is a founder‑level role with meaningful equity upside.
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