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About SentientSentient Foundation is building the cognitive layer of the decentralized web — creating open, composabl...

Ai Engineer Node Remote

$105k - $118k* · Senior Fully remote

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About SentientAt Sentient, we’re pioneering the decentralized artificial general intelligence (AGI) frontier, breakin...

Engineer Front End Blockchain Docker

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AI Engineer

Sentient Remote

Live

$105k - $118k · Senior Full-time Posted 7 months ago 2 min read

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

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