Ripline deploys AI agents so hardware teams in aerospace, defense, energy and telecom land production without operational drag. Backed by Khosla Ventures.
About the role
Member of Technical Staff is a generalist position where you will collaborate closely with the founders on product direction, implementation, and deployments. This role has high autonomy and requires exercising high agency. When you find a thread worth pursuing , you pursue it. Customer experience is supreme and should be the lens in which you problem solve. Own the agent runtime. Scaffold out durable agentic infrastructure for long-horizon tasks. Found on 1752vc Careers, the job board for startup and VC roles.
What they're looking for
- Meaningful product engineering experience in industry
- Strong backend and systems engineering fundamentals with a heavy emphasis on distributed systems
- Deep expertise in agent architectures and LLM-powered applications
- Familiarity with TypeScript, Next.js, and Python
More about this role
Ripline is an applied research lab deploying specialized intelligence in critical industries (i.e. aerospace, defense, and more). Our focus is to deploy agents that automate operational work.
We’re backed by a large seed led by Khosla Ventures (Adrian Radu, Keith Rabois), Hanabi Capital (Shreyan Jain, Mike Volpi), SV Angel , SF1 , and other investors. Our angels include founders/execs at OpenAI, Google DeepMind, Cursor, Decagon, CoreWeave, Profound, Northwood Space, Solidworks, and more.
Member of Technical Staff is a generalist position where you will collaborate closely with the founders on product direction, implementation, and deployments. This role has high autonomy and requires exercising high agency. When you find a thread worth pursuing , you pursue it. Customer experience is supreme and should be the lens in which you problem solve.
Own the agent runtime. Scaffold out durable agentic infrastructure for long-horizon tasks.
Post-training. Create post-training recipes using pipeline RL and make optimizations for max gpu utilization
Context Engineering. Automate ingestion of extremely unstructured and messy enterprise datalakes.
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