Eternis is building systems for a world with highly capable AI.

We envision a world where everyone has a digital twin that understands your preferences, evolves with you, makes millions of decisions daily, and coordinates seamlessly with other twins. While power over AGI and resources consolidates into the hands of a few, we're building a different future—one where billions of digital twins govern powerful multi-agent systems with access to capital, physical resources, and real-world agency.

<aside> ❇️ What we're building:

• Digital twin that is learning based on your interactions, preferences and understands all your data
• Digital twin networks in which twin is a first class citizen filtering information based on human’s preferences
• Secure execution environments for verifiable execution, private storage, and autonomous operation
• Protocols for large-scale coordination between intelligent agents
• The most comprehensive dataset for human-aligned decision-making
• Personalisation, recommendation systems owned collectively by twin networks

About Us: We're a well-funded startup ($30M raised) based in SF.

Stack: Go, Temporal, K8s, Rust, TypeScript (NextJS), AWS Nitro

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Role description

• Self-motivated Go engineer familiar with software engineering and AI patterns
• Able to both hack new projects quickly and scale up existing projects, motivated by product / users in addition to the engineering work itself
• Drive prototyping / MVP development with a fast-paced and experimental process, maintaining the goal of learning from technical obstacles and user feedback, and iterating quickly

Ideal candidate

• You are at a point in your life where you want to make an impact on a global scale, believe this is truly possible by leveraging AI, and are searching for a highly motivated team to make it happen.
• You have a deep sense of urgency and want to solve problems at high speed.
• You use AI tools daily (Cursor, Windsurf, Cline, Devin, Claude Code, Codex or similar)
• You stay up-to-date with the AI ecosystem
  • You know which frontier lab has non-OpenAI compatible API
  • You’re familiar with KV cache
  • You’ve done projects with LLM output streaming
  • You have built an MCP server and understand tool calling
  • You’ve experimented with building voice agents (LiveKit, pipecat, pion or similar frameworks)
  • You’ve reverse engineered the APIs of common products (OpenAI, Sesame, etc.) to gather insights of how to build products better and follow what AI leaders are doing APIs (Google Generative Service)
  • You know enough AI to write good prompts (Chain of Thought)
  • You have experience running LLMs locally
• Best software engineering practices on engineering problems auth, migrations, CI, architecture, eventual consistency, queues, events
• Knowledge of distributed systems (distributed databases, queues, workflow engines like Temporal)

Nice to have experience in

• Temporal
• GraphQL
• Cassandra / Scylla
• Vector databases / RAG projects
• Publications