Staff Software Engineer (Agentic Systems)

We're looking for a highly experienced engineer to join as a founding team member and take technical ownership of core agent infrastructure and ontology systems. This is a hands-on leadership role for someone who thrives in ambiguous environments and wants to build intelligent agentic systems from the ground up.

You’ll work directly with the co-founders and play a central role in the architecture, design, and scalability of our AI infrastructure—especially our reasoning and execution layers.

What You’ll Do

• Architect and build the core agentic infrastructure: Build scalable systems for agent orchestration, task planning, memory, and reasoning using Python and open-source LLM tools (e.g. LangChain, Haystack, LlamaIndex).
• Lead ontology development: Build and evolve the company’s semantic data layer, including automated ontology generation, schema reconciliation, and entity disambiguation across structured and unstructured sources.
• Own the agent runtime: Implement robust planning, execution, and observability logic for distributed, autonomous workflows.
• Build foundational data infra: Develop and maintain our metadata store, data connectors, ETL systems, and vectorized storage layers (e.g. Chroma, Weaviate, or Pinecone).
• Contribute to core AI reasoning systems: Develop task decomposition strategies, tool usage planning, and hybrid LLM + symbolic reasoning pipelines.
• Define the technical culture: Set the bar for code quality, documentation, and system design. Drive hiring, mentoring, and long-term architectural thinking.
• Work across the stack if needed: Comfortable jumping into backend APIs or lightweight frontend tools to ship quickly and iteratively.

What We’re Looking For

• 10+ years experience in high-impact backend, AI infrastructure, or systems roles.
• Expert Python skills, including experience in production environments with LLM tooling, LangChain, agent frameworks, and data processing pipelines.
• Hands-on experience with AI agent architecture with agentic systems in production (planning, tool usage, memory, vector DBs, knowledge graphs).
• Deep experience building and applying ontologies, knowledge graphs, or semantic layers in production.
• Strong understanding of data infrastructure: modern data stacks (e.g. dbt, BigQuery), orchestration (Airflow/Kubernetes), and cloud platforms (GCP or AWS).
• Background in reasoning systems, knowledge representation, or symbolic AI is a huge plus.
• Entrepreneurial mindset with the ability to build independently and make architectural decisions fast.
• Extremely motivated with the ambition to quickly build a generational company solving real problems in ways never tackled before
• 10x engineer that uses AI tools to maximize their output (experience with cursor, windsurf, or similar)