AI Automation Engineer

We're looking for an AI Automation Engineer to build internal AI-powered tools and automated workflows that accelerate every department in the company — from content production to growth to operations.

You'll work directly with the founding team and C-level leadership at a fast-growing startup with the freedom and infrastructure to move fast.
 

Ready to be part of a modern, fast-growing #1 product in its niche and gain extensive professional growth? Apply now!
 

Who are we?

memoryOS makes it easy for people to remember what's important. Proven learning and memory techniques are merged with Duolingo-like gamified e-learning with patented virtual mind palace tech. Co-founded by 2X World Memory Champion — Jonas von Essen.
We're a remote team of 30+ like-minded and diverse professionals, united around solving the problem of the forgetting curve.

We are proud to be the Most Funded App on Kickstarter. memoryOS was featured on TechCrunch and recognized by Google Brands Accelerator as "light years ahead of any other company in memory space."

Your playground

You'll have access to serious local AI infrastructure: 2x Mac Studio M3 Ultra machines, each with 512GB unified memory, running OpenClaw with the strongest open-weight models available — including the latest from Minimax, Qwen, and more. No API rate limits. No vendor lock-in. Full freedom to experiment, fine-tune, and ship.

You'll also work hands-on with cutting-edge tools like Claude Opus 4.6, Autoresearch, and agentic AI frameworks — building real systems, not demos.

What you'll be working on

• Design and build AI-powered internal tools for teams across content, marketing, analytics, and operations
• Architect and maintain automated workflows that multiply output per team member
• Deploy, manage, and optimize local LLMs on our Mac Studio infrastructure via OpenClaw
• Integrate external AI APIs (Anthropic, OpenAI, etc.) where local models aren't the right fit
• Collaborate directly with the CEO and founding team to identify the highest-leverage automation opportunities
• Prototype fast, iterate based on real usage, and ship tools that people actually use daily

About you 

• 2+ years of hands-on experience building with LLMs (local and API-based)
• Strong Python skills; comfortable with FastAPI, scripting, and glue code that holds up in production
• Experience deploying and running open-weight models locally (llama.cpp, vLLM, Ollama, or similar)
• Familiarity with prompt engineering, RAG pipelines, and agentic workflows
• Feel of urgency towards shipping — you'd rather deploy something useful today than architect something perfect next quarter

Will be a plus

• Experience with n8n, Make, or similar workflow automation platforms
• Familiarity with Apple Silicon / Metal optimization for ML workloads
• Background in building internal tools or developer platforms
• Experience with multi-agent systems or orchestration frameworks
• Contributions to open-source AI projects
• Comfortable working autonomously in a fast-moving startup where priorities shift

You will also get

• Direct access to C-level and founding team — your work shapes company strategy, not just tooling
• A local AI lab that most engineers only dream about (2x Mac Studio M3 Ultra, 512GB each, full model freedom)
• Work at the intersection of AI, learning science, and gamification
• Transparent management and regular feedback
• The opportunities to be involved in interesting and useful product for millions of people.
• Significant opportunities for professional growth and impact
• The modern team of like-minded and diverse professionals.
• Enjoy a vacation and paid sick leave days to relax every year.
• Fully remote: you are free to choose your productive work time and place.

Getting the job

Please send your CV and a brief cover letter explaining:

1. What's the most impactful AI automation or internal tool you've built, and what made it work?
2. Why does memoryOS's mission and this role excite you?

Step-by-step for this position:

1. Screening call with Recruiter (45 min): Position overview, basic competencies, culture fit
2. Technical task: A practical challenge relevant to the role
3. Technical interview with CEO and Technical Product Manager (up to 1.5 hours): Deep-dive into experience, technical skills, and problem-solving approach
4. Referral: Recommendations from previous workplace
5. Final interview with CEO and Technical Product Manager (up to 30 min): Alignment with company strategy
6. Offer call with HR (30 min): Final terms

We look forward to receiving your application!