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Ai In Jobs in California (NOW HIRING)

Androcles-Group

People AI Lead

San Jose, CA

Qualifications * Experience: 7+ years in People Operations, HR Tech, Talent Strategy, or People Transformation Consulting. * AI Expertise: Demonstrated success implementing AI/LLM solutions ...

Lattice Partners

Product Designer, AI

Los Angeles, CA · On-site

$150K/yr

We operate across all industries, with clients in entertainment, finance, and manufacturing. As a product studio, we build 0→1 AI products for clients starting businesses and for ourselves. We do ...

Qualified Health

Applied AI Engineer

Palo Alto, CA · On-site

$180K - $250K/yr

Join us in shaping the future of healthcare. Job Summary: We're hiring an Applied AI Engineer to focus on building and scaling real-world AI workflows. This role is designed for engineers who are ...

Hippocratic AI

Senior Staff AI Engineer

Menlo Park, CA · On-site

$65 - $84/hr

About Us Hippocratic AI is the leading generative AI company in healthcare. We have the only system that can have safe, autonomous, clinical conversations with patients. We have trained our own LLMs ...

Hippocratic AI

Senior Staff AI Engineer

Menlo Park, CA · On-site

$65 - $84/hr

About Us Hippocratic AI is the leading generative AI company in healthcare. We have the only system that can have safe, autonomous, clinical conversations with patients. We have trained our own LLMs ...

Hippocratic AI

Senior Staff AI Engineer

Menlo Park, CA · On-site

$290 - $420/hr

About Us Hippocratic AI is the leading generative AI company in healthcare. We have the only system that can have safe, autonomous, clinical conversations with patients. We have trained our own LLMs ...

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All JobsAi In JobsAi In Jobs in California

Ai In information

What is the difference between Ai In vs Data Analyst?

AspectAi InData Analyst
Required CredentialsTypically a degree in AI, computer science, or related field; certifications in AI or machine learningDegree in statistics, mathematics, or related field; certifications in data analysis or visualization
Work EnvironmentTech companies, AI research labs, startups; focus on developing AI modelsBusiness, finance, healthcare sectors; analyze data to inform decisions
Employer & Industry UsagePrimarily in tech and AI-focused industriesAcross various industries including finance, healthcare, marketing

While both roles involve working with data, Ai In focuses on developing and implementing AI models, whereas Data Analysts interpret data to support business decisions. Ai In roles require specialized knowledge in AI and machine learning, while Data Analysts focus on data visualization and statistical analysis.

What cities in California are hiring for Ai In jobs?

Cities in California with the most Ai In job openings:

Ai In jobs near you
Infographic showing various Ai In job openings in California as of August 2026, with employment types broken down into 76% Full Time, 19% Part Time, 2% Temporary, and 3% Contract. Highlights an 67% Physical, 4% Hybrid, and 29% Remote job distribution.

Lead AI Engineer - Productivity Systems

Nubank

Palo Alto, CA • On-site

Full-time

Medical, Dental, Vision, Life, Retirement

Posted 18 days ago

Job description

About Nu
Nu is the leading digital bank in Latin America, serving 135 million customers across Brazil, Mexico, and Colombia. The company has been leading an industry transformation by leveraging data and proprietary technology to develop innovative products and services.
Guided by its mission to fight complexity and empower people, Nu caters to customers' complete financial journey, promoting financial access and advancement with responsible lending and transparency. The company is powered by an efficient and scalable business model that combines low cost to serve with growing returns.
Nu's impact has been recognized in multiple awards, including Time 100 Most Influential Companies, Fast Company's Most Innovative Companies, and Forbes World's Best Banks.
Visit our Institutional Page
About the Role
We are looking for an engineer who has already built with AI in production. You have shipped LLM-powered systems (agents, copilots, RAG pipelines, or AI-driven automations), you know what breaks when they meet real users, and you know how to make them reliable enough for business-critical workflows.
Your day-to-day is applied AI engineering: designing agentic workflows, integrating LLMs into internal tools and business processes, building evaluation and guardrail layers, and turning manual, high-friction workflows into AI-assisted ones that thousands of Nubankers depend on.
This is not an infrastructure role. You will not spend your days on Terraform, IAM policies, or email deliverability. Cloud fluency helps, but the core of this job is the AI layer - prompts, context, agents, evaluations, integrations - and the product judgment to know where AI genuinely helps versus where deterministic automation is the right answer.
Key Responsibilities
Applied AI & Agentic Systems
  • Design, build, and ship LLM-powered agents and workflows that automate complex internal processes end-to-end.
  • Work hands-on with frontier models and the modern AI stack: tool/function calling, structured outputs, MCP, RAG, multi-agent orchestration.
  • Own the full lifecycle of an AI system: from problem discovery and prototype to production hardening, monitoring, and iteration.

Evaluation & Reliability
  • Build evaluation harnesses, guardrails, and quality feedback loops so AI systems can be trusted in production - not just demoed.
  • Define what "good" looks like for non-deterministic systems and instrument it: evals, regression suites, human-in-the-loop review where it matters.

Intelligent Workflow Automation
  • Use orchestration platforms (e.g., n8n) and custom integrations as delivery vehicles for AI-in-the-loop automation across business units.
  • Integrate enterprise platforms (Slack, Google Workspace, Jira, internal APIs) into coherent, AI-assisted workflows.

AI Adoption & Governance
  • Drive the technical strategy for AI adoption within engineering and business workflows.
  • Develop governance frameworks that make AI coding assistants and agents safe, compliant, and effective - balancing developer freedom with security and operational risk.

Multiplier Work
  • Create Golden Paths, reference implementations, and documentation that let other teams build AI workflows safely on their own.
  • For Lead/IC6: act as the technical reference for applied AI in the domain, influence architecture beyond the immediate team, mentor senior engineers, and partner with ITSec and Privacy to align AI solutions with company policy.
  • For Senior/IC5: execute complex AI projects with high autonomy, identify workflow bottlenecks worth automating, and mentor mid-level engineers.
What are we looking for?
Must Have - Demonstrated Applied AI Experience
  • Shipped LLM systems in production: at least one real system with an LLM at its core - an agent, copilot, RAG application, or AI-driven automation - used by real users, not a proof of concept.
  • Hands-on AI engineering: practical fluency with prompt and context engineering, tool/function calling, structured outputs, and agent frameworks or orchestration patterns.
  • Evaluation mindset: experience measuring and improving AI output quality - evals, test sets, feedback loops - and an honest understanding of failure modes (hallucination, drift, prompt injection).
  • Solid software engineering foundation: proficiency in Python, TypeScript, or Clojure; strong API and integration skills; the discipline to ship maintainable systems, not notebooks.
  • AI product sense: the judgment to identify which problems deserve an LLM, which need deterministic automation, and which should not be automated at all.

Nice to Have
  • Experience with workflow automation platforms (n8n, Zapier, or custom orchestration engines).
  • Exposure to cloud services (AWS) and infrastructure-as-code.
  • Familiarity with AI developer tooling (Claude Code, Cursor, Copilot) and AI governance practices.

Behavioral & Strategic Skills
  • Builder bias: you prototype fast, validate with real users, and harden what works.
  • Governance-aware: you understand that "efficiency" must be balanced with "security," and you can design AI systems that are safe by default without destroying velocity.
  • Multiplier: you enjoy documenting your work, creating Golden Paths, and teaching others how to use what you build.
  • Comfortable with ambiguity: AI capabilities shift monthly; you treat that as an opportunity to re-solve problems better, not as churn.

Location
  • Miami, United States
  • Palo Alto, United States
  • Washington DC, United States
Our Benefits
  • Opportunity of earning equity at Nu
  • Medical Insurance
  • Dental and Vision Insurance
  • Life Insurance and AD&D
  • Extended maternity and paternity leaves
  • Nucleo - Our learning platform of courses
  • NuLanguage - Our language learning program
  • NuCare - Our mental health and wellness assistance program
  • 401K
  • Saving Plans - Health Saving Account and Flexible Spending Account
  • Work-from-home Allowance
  • Relocation Assistance Package, if applicable.
Work Model for this Role
Hybrid 2-3 times/week: Our hybrid work model brings us to the office at least twice a week, on strategic days designed to maximize team connection and collaboration. For more details, visit https://building.nubank.com/nu-hybrid-work-model/
Location-Specific Disclosures
  • Palo Alto: Total compensation includes base salary, RSUs and benefits. Base salary range: $11,712 - $17,568

Our recruitment process may involve the use of artificial intelligence-enabled tools, such as automated interview transcription and analysis, to support the evaluation process. Artificial intelligence is not used to make final hiring decisions; all decisions are made by human reviewers.

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