2

Entry Level Ai Agent Developer Jobs in California

Sphere, starting with engineering and expanding into ops, customer success, tax research, and implementation workflows. WHAT YOU'LL DO Within days * Ship AI agent features that help Sphere ...

In this role, you will design, develop, and deploy advanced LLM and AI Agent technologies that ... Design and improve prompt engineering and context engineering workflows, including AI evaluation ...

In this role, you will design, develop, and deploy advanced LLM and AI Agent technologies that ... Design and improve prompt engineering and context engineering workflows, including AI evaluation ...

In this role, you will design, develop, and deploy advanced LLM and AI Agent technologies that ... engineering workflows, including AI evaluation, debugging, and tuning for real-world product ...

You'll work alongside senior engineers, product managers, and AI researchers to build systems that ... learning about multi-agent architectures, fine-tuning workflows, and evaluation techniques.

You'll work alongside senior engineers, product managers, and AI researchers to build systems that ... learning about multi-agent architectures, fine-tuning workflows, and evaluation techniques.

Applied AI Agent

Sunnyvale, CA · On-site

$179K - $220K/yr

You'll work alongside senior engineers, product managers, and AI researchers to build systems that ... learning about multi-agent architectures, fine-tuning workflows, and evaluation techniques.

Each AI Agent is purpose-built for a specific role, equipped to understand context, make decisions ... This is an entry-level role suitable for a recent graduate or an engineer with up to three years of ...

Familiarity with mainstream Agent architectures (e.g., ReAct/PlanAct), Multi-Agent systems, and concepts such as Context Engineering and Memory. - Solid AI/ML background with in-depth knowledge of ...

Familiarity with mainstream Agent architectures (e.g., ReAct/PlanAct), Multi-Agent systems, and concepts such as Context Engineering and Memory. - Solid AI/ML background with in-depth knowledge of ...

Senior AI Engineer

San Francisco, CA · On-site

$123K - $169K/yr

We're looking for a Senior AI engineer to build the core intelligence behind AI teammates for ... Familiarity with AI agent frameworks and orchestration patterns * Experience integrating AI into ...

Showing results 41-60

Entry Level Ai Agent Developer information

What is an entry level AI agent developer?

Entry Level AI Agent Developers are professionals who assist in designing, building, and maintaining artificial intelligence agents, such as chatbots or virtual assistants, often under the supervision of more experienced engineers. They typically work with programming languages like Python and use machine learning frameworks to help create intelligent systems that can interact with users or perform tasks autonomously. These roles are suited for those new to the field and often require a foundational understanding of AI concepts, basic coding skills, and a willingness to learn advanced topics on the job.

What does an entry level AI agent developer do?

As an Entry Level AI Agent Developer, you can expect to work on tasks such as building and fine-tuning conversational AI agents, assisting with data preprocessing, and implementing basic machine learning models under the guidance of senior engineers. You’ll likely contribute to updating or troubleshooting existing AI agents, performing code reviews, and writing test cases. Collaboration with data scientists, UX designers, and product managers is common, giving you exposure to the full development lifecycle and valuable opportunities to learn from experienced colleagues.

What are the key skills and qualifications needed to thrive as an entry level AI agent developer?

To thrive as an Entry Level AI Agent Developer, you need a solid understanding of programming languages (such as Python), basic machine learning concepts, and a relevant degree in computer science or a related field. Familiarity with AI frameworks (like TensorFlow or PyTorch), API integration, and version control systems (e.g., Git) is typically required. Problem-solving ability, eagerness to learn, and effective teamwork are standout soft skills for this role. These skills and qualities are vital for building, maintaining, and improving AI agents in a collaborative and rapidly evolving tech environment.

What is the difference between Entry Level Ai Agent Developer vs Data Analyst?

AspectEntry Level Ai Agent DeveloperData Analyst
Required CredentialsBachelor's in CS, AI, or related field; basic programming skillsBachelor's in Statistics, Math, or related field; data analysis skills
Work EnvironmentTech companies, AI startups, R&D labsBusiness, finance, healthcare sectors
Employer & Industry UsageDeveloping AI agents, chatbots, automation toolsInterpreting data, creating reports, supporting decision-making

Entry Level Ai Agent Developers focus on creating and refining AI agents and chatbots, often requiring programming and AI knowledge. Data Analysts interpret data to inform business decisions, typically with statistical skills. While both roles involve data and technology, they serve different functions within organizations. The choice depends on your interest in AI development versus data interpretation.

What are the most commonly searched types of Ai Agent Developer jobs in California?

The most popular types of Ai Agent Developer jobs in California are:

What are popular job titles related to Entry Level Ai Agent Developer jobs in California?

For Entry Level Ai Agent Developer jobs in California, the most frequently searched job titles are:

What job categories do people searching Entry Level Ai Agent Developer jobs in California look for?

The top searched job categories for Entry Level Ai Agent Developer jobs in California are:

What cities in California are hiring for Entry Level Ai Agent Developer jobs?

Cities in California with the most Entry Level Ai Agent Developer job openings:

Infographic showing various Entry Level Ai Agent Developer job openings in California as of August 2026, with employment types broken down into 91% Full Time, and 9% Part Time. Highlights an 91% In-person, and 9% Remote job distribution.

AI Agent Infrastructure Lead

Sphere

San Francisco, CA • On-site

$230K - $260K/yr

Full-time

Re-posted 23 days ago


Job description

ABOUT SPHERE
Every breakthrough in trade infrastructure has followed the same pattern: reduce a transaction cost, expand the market. Containerization for goods. SWIFT for money. Stripe for payments. Compliance is one of the last and largest - and the hardest, because trade rules aren't data to be looked up. They're a complex adaptive system with 190+ sovereign jurisdictions, in different languages, changing constantly, reacting to each other.
Sphere built the system that solves it. Our AI (TRAM) ingests global trade law, interprets it, resolves conflicts across jurisdictions, and produces compliance determinations more reliable than human experts. We handle the entire lifecycle - calculation, registration, filing, remittance - at millisecond latency with zero downtime.
  • Backed by a16z and YC. $21M Series A, 30%+ month-over-month growth, customers include ElevenLabs, Replit, Deel, Runway, and Lovable.
  • Small team, global surface area. Everyone owns a domain that would be a full team at a larger company. San Francisco, five days in office.
  • The problem keeps compounding. Expanding into input tax, withholding, e-invoicing, tariffs - each multiplies the complexity. Tens of millions of transactions today, billions ahead.

THE ROLE
Sphere is looking for an engineer to lead our internal AI agent enablement efforts. You'll build the systems that let AI agents safely and effectively increase velocity across. Sphere, starting with engineering and expanding into ops, customer success, tax research, and implementation workflows.
WHAT YOU'LL DO
Within days
  • Ship AI agent features that help Sphere's engineering team use agents more effectively and responsibly.
  • Iterate on versions of Sphere's agent sandbox environments.
  • Create workflows where agents can inspect the codebase, run local infrastructure, make changes, run tests, and prepare work for human review.
  • Work directly with engineers to identify high-leverage internal workflows where agents can create immediate velocity.

Within months
  • Lead Sphere's internal efforts to enable AI agents to act more autonomously across engineering, ops, customer success, tax research, and implementation.
  • Build "Goose" for Sphere: the internal AI agent layer that helps agents understand and operate across Sphere's systems.
  • Own the infrastructure, tooling, and workflows that let agents safely take on more complex internal work over time.
  • Establish the patterns for how Sphere uses agents internally, including context, permissions, review, observability, and escalation.

REQUIREMENTS
  • Experience building production-quality software.
  • Experience in AI agents, coding agents, internal developer tooling, or AI agent enablement.
  • Comfort working across backend systems, infrastructure, local development environments, CI, and internal tools.
  • Strong judgment around autonomy, safety, permissions, and human review.
  • High agency. You can take a vague internal problem and turn it into a working system people actually use.
  • Strong attention to detail. Agents are only useful here if they improve speed without reducing correctness.

WHO YOU ARE
You'll thrive here if:
  • You're a Dog. You've been underestimated, gone through struggle, and never stopped running. You have a chip on your shoulder and enormous drive. You look at Stripe, Deel, and Flexport all punting on compliance and think: good, that means the opportunity is ours. Hunger beats pedigree.
  • Early stage is in your bones. You've built things where there's no playbook and nobody handing you the answer. You define the problem instead of waiting for instructions.
  • You own it end to end. Give you a goal and you figure out your own path. Small team, global surface area - everyone owns a domain that would be a full team at a larger company. No one tells you how.
  • You believe speed and accuracy are both possible. We're building a complex product that requires robustness and 100% uptime, and we have to build at our customers' pace. Move fast. Don't break things. Both.

This won't be a fit if:
  • You need structure handed to you or ambiguity feels draining rather than motivating
  • You want to manage people more than own hard problems (we're a flat, experienced team - everyone builds)
  • You're used to "good enough" shipping (small errors have outsized impact here)