Remote Jobs at Sentient
There are 3 Web3 Jobs at Sentient
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| Job Position | Company | Posted | Location | Salary | Tags |
|---|---|---|---|---|---|
Sentient | Remote | $105k - $118k | |||
Sentient | Remote | $90k - $96k | |||
Sentient | United States | $36k - $65k |
About Sentient
Sentient Foundation is building the cognitive layer of the decentralized web — creating open, composable, agent-based AI systems that serve humanity, not platforms. Our flagship product, Sentient Chat, is a generative AI assistant powered by open-source models and governed by its users. We operate at the frontier of AI, Web3, and open innovation.
The Role
We’re looking for a Senior AI Engineer with a strong foundation in backend development and a proven track record of shipping real-world GenAI systems. You’ll work at the heart of Sentient’s AI stack — designing, deploying, and iterating on intelligent agents, RAG pipelines, and LLM-powered features in production.
This is a role for someone who thrives in 0→1 environments, loves working with state-of-the-art AI frameworks, and wants to help shape the future of decentralized intelligence.
What You’ll Do
• Design, build, and scale production-grade GenAI agents
• Work with LLM frameworks, agentic systems, RAG pipelines, and eval tooling
• Build backend services and APIs that power Sentient Chat and future AI-native products
• Collaborate with researchers, infra engineers, and product teams to ship iteratively and intelligently
• Help define best practices for prompt engineering, model selection, and continuous evaluation
• Stay close to the bleeding edge of AI, testing and integrating advances quickly
What We’re Looking For
• 5–10 years of backend software engineering experience (Python, Node.js, Go, or similar)
• 2–4 years working directly with Generative AI systems (LLMs, diffusion models, or agents)
• Proven experience with:
• Agentic frameworks (LangChain, AutoGen, CrewAI, etc.)
• Retrieval-augmented generation (RAG) and semantic search
• Prompt design, task decomposition, and evaluation pipelines
• Understanding of scalable infrastructure and deploying AI in production
• Bonus: experience with model training, fine-tuning, or hosting open-source LLMs (vLLM, LoRA, etc.)
• A builder’s mindset — curious, fast-moving, and unafraid of ambiguity