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Chatbot Developer Jobs in Dublin, CA (NOW HIRING)

AGI, Inc.

AI Engineer - Backend

San Francisco, CA · On-site

$120 - $150/hr

... like a chatbot. You'll own the systems that turn research into product -- model orchestration ... This is for the backend engineer who has been the on-call hero before, who has strong opinions ...

Drata

Platform Engineer, AI Tooling

San Francisco, CA · On-site

$131.90 - $178.50/hr

... on the Developer Experience Team (part of Foundation Engineering group) will help build the ... not just chatbot prompts * Strong backend skills: TypeScript or Python in production, REST APIs ...

Walmart

(USA) Staff, Data Engineer

Hayward, CA · On-site

$143K - $286K/yr

As a Staff Data Engineer at Walmart, you will design and implement scalable data solutions that ... The team also advances health-focused web pages and chatbot features that helps in the health ...

Walmart

(USA) Staff, Data Engineer

San Jose, CA · On-site

$143K - $286K/yr

As a Staff Data Engineer at Walmart, you will design and implement scalable data solutions that ... The team also advances health-focused web pages and chatbot features that helps in the health ...

Walmart

(USA) Staff, Data Engineer

Milpitas, CA · On-site

$143K - $286K/yr

As a Staff Data Engineer at Walmart, you will design and implement scalable data solutions that ... The team also advances health-focused web pages and chatbot features that helps in the health ...

Spellbrush

3D Game Programmer (Unity)

San Francisco, CA · On-site

Think MiSide with LLMs, but truly integrated with gameplay, not just a RP chatbot. About Us Here at ... We're looking for a strong Unity engineer who loves 3D story-driven games. You'll join our lead ...

daydream Labs, Inc

Applied AI Engineer

San Francisco, CA · On-site

$160K - $260K/yr

We are not building a chatbot. We are building an employee. Why us We ran an SEO agency before ... The Engineering Challenge Fully autonomous agents are still mostly unsolved. sunbeam has to plan ...

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All JobsChatbot Developer JobsChatbot Developer Jobs in Dublin, CA

Chatbot Developer information

See Dublin, CA salary details

$83.9K

$105.6K

$142.5K

How much do chatbot developer jobs pay per year?

As of Aug 23, 2026, the average yearly pay for chatbot developer in Dublin, CA is $105,581.00, according to ZipRecruiter salary data. Most workers in this role earn between $90,100.00 and $107,000.00 per year, depending on experience, location, and employer.

What is a chatbot developer?

Chatbot Developers are professionals who design, build, and maintain conversational programs, often using artificial intelligence or scripted logic, to interact with users via messaging platforms, websites, or apps. They work with programming languages, natural language processing (NLP), and machine learning frameworks to create chatbots that can answer questions, provide customer support, or automate tasks. Their role involves understanding user needs, integrating chatbots with existing systems, and ensuring a seamless, human-like conversational experience.

What does a chatbot developer do?

As a chatbot developer, you create applications that automate customer services or other communication processes. You design programs that use artificial intelligence to communicate with humans via text or audio. You develop chatbot programs so that they can communicate in a variety of scenarios. You test your application and debug it if necessary. Your duties include reviewing and simplifying code when needed. As a chatbot developer, you may also help companies implement bots in their operations. You often work with established AI platforms such as Microsoft Azure Cognitive Services and use a variety of computer languages, including Python, C++, and JavaScript.

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

To thrive as a Chatbot Developer, you need expertise in programming languages like Python or JavaScript, a solid understanding of natural language processing (NLP), and experience with chatbot frameworks such as Dialogflow or Microsoft Bot Framework. Familiarity with cloud platforms, APIs, and version control systems (e.g., Git) is also commonly required, along with certifications in AI or related fields being advantageous. Strong problem-solving skills, creativity, and effective communication help developers design user-friendly and intuitive conversational experiences. These skills ensure the creation of reliable, scalable, and engaging chatbots that effectively address user needs and business goals.

What are some common challenges chatbot developers face when integrating chatbots with existing systems?

One common challenge Chatbot Developers encounter is ensuring seamless integration of chatbots with legacy systems and diverse databases, which may have inconsistent data formats or limited APIs. Developers often need to troubleshoot compatibility issues, manage security protocols, and handle real-time data synchronization. Close collaboration with IT teams and clear documentation are essential for successful integration and ongoing maintenance. Overcoming these challenges can lead to more robust and scalable chatbot solutions.

What is the difference between Chatbot Developer vs AI Developer?

AspectChatbot DeveloperAI Developer
Required CredentialsProgramming skills, knowledge of chatbot platforms, basic AI understandingAdvanced AI/ML certifications, programming, data science background
Work EnvironmentTech companies, customer service, e-commerce, startupsResearch labs, tech firms, industries applying AI solutions
Employer & Industry UsageFocus on conversational interfaces, customer engagementBroader AI applications, including machine learning, NLP, robotics
Search & Comparison IntentUnderstanding chatbot roles, skills, and job scopeExploring broader AI career paths and skills

While both roles involve AI concepts, a Chatbot Developer specializes in creating conversational interfaces for customer engagement, whereas an AI Developer works on broader artificial intelligence applications, including machine learning and data analysis. The roles share overlapping skills but differ in scope and industry focus.

How much do chatbot developers make?

Chatbot developers typically earn between $70,000 and $120,000 annually, depending on experience, location, and skill level. Entry-level positions may start lower, while experienced developers with expertise in AI, natural language processing, and programming languages like Python or JavaScript can earn higher salaries.

Is a chatbot developer a good career?

A chatbot developer is a viable career choice as it involves designing and implementing conversational AI using programming languages, natural language processing, and machine learning tools. The demand for chatbot developers is growing across industries such as customer service, healthcare, and finance, offering opportunities for specialization and career advancement.
More about Chatbot Developer jobs

What cities near Dublin, CA are hiring for Chatbot Developer jobs?

Cities near Dublin, CA with the most Chatbot Developer job openings:

Chatbot Developer jobs near you
Infographic showing various Chatbot Developer job openings in Dublin, CA as of August 2026, with employment types broken down into 79% Full Time, 8% Part Time, and 13% Contract. Highlights an 80% Physical, 6% Hybrid, and 14% Remote job distribution, with an average salary of $105,581 per year, or $50.8 per hour.

AI Engineer - Backend

AGI, Inc.

San Francisco, CA • On-site

$120 - $150/hr

Other

Re-posted 27 days ago

Job description

Think Different. Build the Future. Our Mission

Build everyday AGI. Trustworthy, consumer-grade agents that redefine human–AI collaboration for millions. Software shouldn’t wait for commands; it should partner with you, amplifying what you can do every single day.

Why AGI, Inc.

We’re a stealth team of elite founders and AI researchers, with backgrounds spanning Stanford, OpenAI, and DeepMind. We’re industry leaders in mobile and computer-use agents, bringing these capabilities to consumer scale.

Grounded in years of agent research, our AI is designed with trustworthiness and reliability as core pillars, not afterthoughts.

We are supported by tier-1 investors who funded the first generation of AI giants; now they’re backing us to build the next: everyday AGI. (Watch the demo)

If you see possibility where others see limits, read on.

Build the systems our agents run on. Make them feel like magic, not infrastructure.

Our agents are only as trustworthy as the backend behind them. Every API call, every retry, every queued job is the difference between an agent that feels alive and one that feels like a chatbot. You'll own the systems that turn research into product — model orchestration, agent state, partner integrations, the data plane — and you'll make them fast enough, observable enough, and boring enough that the rest of the team can ship without thinking about them.

This is for the backend engineer who has been the on-call hero before, who has strong opinions about queues and idempotency, and who wants to design infrastructure for a product where the floor is "millions of devices."

Tasks you will own
  • The agent backend end-to-end — model orchestration, tool-use plumbing, agent state, retries, observability
  • The data plane behind every agent action — Postgres schema, caching, queues, event streams — at OEM scale
  • Production SLAs, on-call, and the reliability bar for everything the agent touches in the cloud
Areas where you will assist
  • Research, by shipping their work to real users in days, not quarters — and feeding back what breaks in production
  • Forward-deployed engineers, by giving them backends partners can integrate against without a six-week meeting
  • iOS and Android, by drawing the right line between on-device and cloud so neither side carries the wrong weight
Skills you'll be expected to teach
  • How to design backends for LLM-powered systems where latency, cost, and non-determinism are first-class concerns
  • How to run a production system you'd happily put your name on — observability, incident response, capacity planning
Skills you'll be expected to learn
  • The internals of agentic systems from the people who published the canonical papers on them
  • What it takes to run agent infrastructure at OEM scale, across Samsung, OPPO, Lenovo, and Vertu devices
  • On-device / cloud co-design — when to push compute to the phone and when to keep it on our side
Timeline of success

After 30 days — You've shipped a meaningful change to the agent backend that a user would feel — latency, reliability, or a new capability. You can name the three weakest links in our infra and have started fixing one. You've taken a real on-call shift.

After 60 days — You own a major surface of the backend. A research breakthrough has shipped through systems you designed. Other engineers route their hardest backend questions to you. You've set the reliability and observability bar that new services have to meet.

After 90 days — Our agent backend is something you'd happily defend to an infra engineer at a top-tier consumer company. You've shaped the architecture for one of our partner launches and have a strong, opinionated plan for what our infra needs to look like to support 10M devices.

Compensation

Competitive cash and meaningful equity. Top-tier relocation and immigration support. SF, in person.

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