Applied AI Engineer

About sunbeam

sunbeam is building a fully autonomous SEO agent that plans, writes, and ships work end-to-end. An agent that ships work is one of the harder problems in applied AI right now. It requires reasoning over long horizons, executing reliably across systems, and owning outcomes that real customers can stake their growth on.

We believe getting this right is a game-changer for how SEO gets done.

sunbeam was built inside daydream, an AI-native SEO agency that runs SEO end-to-end for companies like Anthropic, Clay, and Replit. We are distilling what daydream learned doing the work into an autonomous agent that does the work on its own.

We've raised over $20M from First Round Capital, Basis Set Ventures, WndrCo, and SOMA Capital, and are backed by leaders from Notion, Airtable, Webflow, and Dropbox, including Lenny Rachitsky and Eli Schwartz, author of Product-Led SEO.

The team

You'll work closely with a small, highly capable team across engineering and design:

• Shravan (CTO), formerly an Engineering Lead at Flixed and a Software Engineer at Facebook, where he worked on mass-scale web scraping for Facebook Jobs and Meta Reality Labs.

• Vishruth (Founding Applied AI Engineer), previously a Data Scientist at Klaviyo specializing in NLP, with a research background from Cornell.

• Daniel (Founding Applied AI Engineer), formerly a Data Engineer on Tesla's Autopilot team and previously Lead Data Engineer at Replit.

• Tom (Founding Designer), who previously led product design at Blockless and now leads our frontend efforts.

How you’ll make an impact

As an Applied AI Engineer at sunbeam, you’ll help build the core intelligence behind the SEO agent that powers our operating model.

You’ll work on systems that translate expert SEO judgment into production-grade AI workflows that plan work, generate materials, and drive continuous execution. You’ll own problems end-to-end—from framing and design through deployment and iteration—and see your work directly drive customer outcomes.

In this role, you will:

• Design, build, and operate LLM-driven systems that prioritize and drive SEO work

• Encode human expertise into structured, repeatable AI workflows

• Architect and optimize complex LLM pipelines for accuracy, reliability, and cost

• Build evaluation frameworks that measure quality and real-world performance

• Collaborate closely with engineers, designers, and Growth Leads to integrate AI into execution

• Ship quickly, then iterate based on feedback from production usage

• Work primarily across LLM-driven systems, data pipelines, and AI-enabled services, using Python, TypeScript, and C#, deployed on Google Cloud with modern foundation models

Minimum Qualifications

• Strong experience building production AI or machine learning systems

• Hands-on experience working with LLMs beyond basic API usage

• Solid understanding of NLP concepts such as embeddings, retrieval, and generation

• Experience owning systems end-to-end, including design, implementation, and iteration

• Comfort operating in ambiguous problem spaces and making sound technical tradeoffs

Preferred Qualifications

• Deep expertise in NLP or applied machine learning

• Strong mental models of transformer-based architectures and modern language models

• Experience designing evaluation methodologies for AI systems

• Familiarity with probabilistic modeling, algorithms, or statistical inference

• Experience translating domain expertise into scalable software systems

• A high bar for correctness, reliability, and operational quality

Position Location

This role is based in San Francisco and requires in-person collaboration five (5) days per week. We offer paid relocation for candidates outside the San Francisco Bay Area.

Compensation

The base salary range for this role is $180,000–$220,000, depending on experience, along with meaningful equity.

What you’ll love

• Health coverage includes medical, dental, and vision with HSA and FSA options, plus One Medical, Talkspace, and Teladoc

• Commuter benefit includes a monthly reimbursement to support your commute to the office

• Meals on us include lunch reimbursement on in-office days, with dinner covered when you’re working late

• Personal well-being includes an annual stipend for gym, fitness classes, therapy, and wellness expenses

• Learning and development includes an annual stipend for books, courses, and classes to support your growth

• Team retreats include two company retreats per year to connect, collaborate, and reset

• Monthly team time includes regular dinners and outings to spend time together

• Dog-friendly office (we have corgis)