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AI Solutions Architect
About Humanoid
Humanoid is a fast-growing humanoid robotics startup building the next generation of intelligent robotic systems. As the company scales, we are investing in AI-powered internal automation, knowledge systems, and decision-support capabilities that enable leadership and teams to operate with greater speed, clarity, and efficiency.
We are looking for an experienced AI Solutions Architect to lead the design and implementation of company-wide AI systems and automation infrastructure.
The Role
You will own the architecture and delivery of Humanoid's internal AI ecosystem, working closely with company leadership, engineering teams, and business stakeholders.
Your mission is to transform fragmented company knowledge, meetings, tasks, and operational processes into a scalable AI-powered platform that provides actionable insights, automates workflows, and enables better decision-making across the organization.
This is a highly hands-on role. You will not only define architecture and technical standards but also personally build the most critical and high-risk components while leading and mentoring an AI Engineer.
What You’ll Do
Requirements Discovery & Business Alignment
- Partner with the CEO and department leaders to identify high-value AI use cases.
- Gather, structure, and prioritize business requirements.
- Translate operational challenges into measurable AI solutions.
- Define acceptance criteria and success metrics for every initiative.
AI Platform Architecture
- Design the architecture for Humanoid's internal AI systems and automation platform.
- Define agent architecture, orchestration patterns, memory systems, retrieval pipelines, and human-in-the-loop workflows.
- Build scalable and maintainable AI solutions following pragmatic MVP principles.
- Ensure solutions remain simple, reliable, and aligned with business needs.
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Data & Knowledge Systems
- Design company-wide knowledge and retrieval systems.
- Build and optimize RAG and hybrid-search architectures.
- Integrate structured and unstructured enterprise data sources, including:
- Slack
- Atlassian/Jira
- Meeting transcripts
- Internal documentation
- Team directories
- Corporate databases
Engineering & Delivery
- Personally implement the most complex and business-critical components.
- Establish engineering standards, code quality expectations, and testing practices.
- Review and validate the work of the AI Engineer.
- Define measurable quality benchmarks for extraction, retrieval, and agent performance.
Enterprise Integration
- Collaborate with internal engineering teams on:
- Technology stack and infrastructure
- System access and permissions
- Security and compliance requirements
- SSO
- Internal platforms
- Enterprise services
API & Contract Design
- Define and maintain APIs and MCP-based interfaces between systems.
- Ensure clear ownership boundaries between domains.
- Enable secure access to company data through well-defined contracts rather than data duplication.
What We’re Looking For
- 5+ years of experience designing and delivering production-grade software systems.
- Proven experience building and deploying AI/LLM-powered products used by real users.
- Strong experience with multi-agent systems and AI orchestration frameworks.
- Deep understanding of:
- RAG architectures
- Vector databases
- Hybrid search
- Knowledge management systems
- LLM evaluation and quality measurement
- Experience integrating AI systems into enterprise environments.
- Strong software engineering background with the ability to personally write production code.
- Experience with APIs, distributed systems, and cloud infrastructure.
- Ability to collaborate effectively with both technical and non-technical stakeholders.
- Strong analytical and problem-solving skills.
- Fluent English communication skills.
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Nice to Have
- Experience in early-stage startups and fast-paced environments.
- Experience building company-wide knowledge platforms and enterprise search systems.
- Familiarity with:
- LangGraph
- Mastra
- n8n
- MCP ecosystem
- Modern agent frameworks
- Experience with access-controlled enterprise knowledge retrieval systems.
- Previous experience supporting executive decision-making systems or internal AI copilots.
What Success Looks Like
Within the first months, you will have built the foundation for Humanoid's internal AI platform: a reliable, scalable system that turns company knowledge, meetings, tasks, and operational data into actionable intelligence for leadership and teams.
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