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Pear VC

Founding Engineer - FlowGen Labs

San Francisco Bay Area$160k–$250kfulltimemidAdded 1 month ago

About this role

FlowGen Labs is seeking a Founding Engineer to develop a unique platform aimed at resolving complex software challenges for large enterprises. This role will involve building infrastructure, engaging directly with customers, and significantly impacting the company's growth and culture in a fast-paced environment.

What you'll do

  • Design and implement an agentic software layer
  • Oversee complex workflows and AI-driven retrieval systems
  • Establish low-latency inference paths and observability
  • Productionize AI prompt pipelines and fine-tuning processes
  • Collaborate with customers on pivotal projects
  • Contribute to defining company culture and engineering standards

What they're looking for

  • Experience in software design and implementation
  • Familiarity with AI tools and development pipelines
  • Strong communication and decision-making abilities
  • Ability to learn new technologies quickly
  • Expertise in orchestrating agentic workflows
  • Understanding of program analysis and code generation
  • Ownership mentality and fast-paced execution

Benefits

  • Meaningful equity in a growing startup
  • High impact on product and company direction
  • Minimal bureaucracy
  • Collaborative and talent-dense environment
  • Visa support available
  • Competitive compensation package
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Pear VC

Pear VC invests in and supports AI-driven enterprise software companies building automation platforms, compliance systems, and specialized tools across industries like financial services, insurance, and software development. The portfolio companies are hiring founding and senior engineers to design core infrastructure, build AI systems, and develop scalable backend platforms alongside their leadership teams.

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Likely interview questions

  • Walk us through a time you built an agentic system or multi-step AI workflow. How did you handle verification and prevent hallucinations?
  • Describe your experience with LLM orchestration frameworks like LangGraph or similar. What worked well and what were the gotchas?
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