Davidjoseph Co logo
Salary
$201K–$240K
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United States
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About the Company

Our client is a well-funded, Series B enterprise AI company headquartered in San Francisco. They build AI agents that discover how work actually happens across an organization, structure it into a living context graph, and improve it continuously for Fortune 500 enterprises. Their customers include some of the world's leading technology companies, and the business has been growing rapidly year over year.

About the Role

We are hiring an AI Backend Engineer to build and own the backend systems that power the company's multimodal AI agents in real enterprise environments. This is a hands-on role at the intersection of distributed systems and applied AI, where you will ship production-grade backend services, own data pipelines, design AI orchestration workflows, and ensure enterprise-grade reliability and security at scale. You will work closely with senior engineers on a small, high-caliber engineering team, own real features from day one, and grow your scope directly with the product.

What You'll Own

  • Design, build, test, and deploy the backend services powering the company's AI platform, from data ingestion and storage through API design, background processing, and deployment architecture
  • Implement AI orchestration pipelines that hold up under real-world variability, working with structured outputs, tool calling, state management, and guardrails to ensure agent reliability at scale
  • Build for enterprise security and scale, including least-privilege access, strong tenant isolation, auditability, and secure data handling across growing customer deployments
  • Balance long-term architectural vision with a relentless shipping cadence, making pragmatic tradeoffs on tech debt with guidance from senior engineers
  • Grow fluency across backend, AI, product, and infrastructure by partnering with teammates from each discipline and turning ambiguous product asks into clean technical specs

Requirements

Must-Have

  • 1 to 3 years of experience shipping production-grade backend systems, or exceptional new graduates with strong portfolios demonstrating real execution
  • Solid fundamentals in backend engineering: services, APIs, data models, and infrastructure designed for reliability, observability, security, and performance
  • Applied AI builder who has shipped at least one meaningful AI-powered project (production, open-source, or a serious side project) and understands the gap between a demo and a reliable system
  • Comfort working in a hands-on, high-ownership environment with senior engineers, taking real features from design through production with increasing autonomy
  • In-person at the San Francisco office 4 days per week (Wednesdays are flexible)

Nice-to-Have

  • Experience with AI orchestration patterns, LLM pipelines, evals, or agentic workflows in production
  • Background working in or alongside full-stack teams, comfortable contributing across the stack when the scope demands it
  • Familiarity with enterprise-grade security requirements: tenant isolation, auditability, least-privilege access
  • AI-native development habits: uses AI tooling fluently across the software development lifecycle to move faster without sacrificing quality

Key Details

  • Location: San Francisco, CA (in-office 4 days per week; Wednesdays flexible)
  • Employment: Full-time
  • Experience: 1–3 years
  • Salary: $201,000 – $240,000 USD per year, plus equity
  • Visa Sponsorship: Available (H-1B, O-1, OPT)

Benefits & Perks

  • Equity in addition to competitive cash compensation
  • 100% employer-paid medical, dental, and vision options
  • Paid parental leave
  • $500 annual learning fund
  • $150 monthly wellness fund
  • 401(k)
  • Relocation support to the San Francisco Bay Area
  • Pre-tax parking and transit account
  • Daily curated local meals delivered to the office, plus drinks and snacks
  • Safe and secure bike room

Interview Process

  1. Application review
  2. Initial screen
  3. Technical interview
  4. System design
  5. Onsite
  6. References
  7. Offer

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