Staff Software Engineer, AI (Org & Governance)

Role Description

We're hiring a Staff Software Engineer to build the AI and agentic engines behind governance at Wand: systems that reason over messy, non-deterministic organizational data to catch policy violations, flag risk, and surface what humans actually need to see. This isn't about using AI day to day. It's about having built it: agentic workflows, models, or systems that went from idea to production.

You'll join the Org Intelligence team as one of its most senior technical voices, with the autonomy to propose an approach, defend it, and then go build it, largely on your own. We're a small, remote-first, high-trust team. There's no hand holding here and not much process either. You own the problem end to end.

Role Responsibilities

• Design and build AI and agentic systems that analyze organizational data to catch policy violations, compliance risks, and governance issues, often from ambiguous, non-deterministic signals.
• Build agents and pipelines that use LLMs to reason over large volumes of data, going well beyond deterministic, rule based checks.
• Architect and build knowledge graph systems that model organizational structure and relationships, and make that context usable by agents.
• Take a fuzzy, undefined problem ("find policy violations across messy data"), propose a real technical approach, defend it, then build it with minimal oversight.
• Bring engineering rigor to inherently fuzzy territory: testing, evaluating, and iterating on how well your agents actually perform.
• Partner with the rest of the Org Intelligence team to get AI-driven insight into the product's governance and compliance surfaces.
• Contribute across the stack when it helps, though the core of this role is the AI and agent layer, not the UI.

Qualifications

• A track record of building AI systems as a creator, not a consumer.
• Experience building or working with knowledge graphs in a real, shipped system.
• Experience building agents or LLM based systems that reason over unstructured or ambiguous data.
• Comfortable owning a project from architecture to delivery with real autonomy.
• Strong software engineering fundamentals and the independence to thrive in a fast moving, remote first, senior-heavy team.
• A history of turning fuzzy, non-trivial problems into concrete, working systems.
• Practical experience with knowledge graph tooling: graph databases and query languages such as Neo4j/Cypher, RDF/SPARQL, Amazon Neptune, or similar.
• Hands on experience with LLM provider APIs (OpenAI, Anthropic, or similar) and agent frameworks such as LangChain or LangGraph.
• Comfortable with retrieval infrastructure like vector databases (Pinecone, Weaviate, pgvector, or similar) for grounding agent reasoning in organizational data.
• Strong in a language well suited to graph construction, agent pipelines, and data analysis.

Preferred Experience

• Experience building security, risk, or compliance related tooling, especially anything involving policy or violation detection.
• Prior experience at a company building agentic or AI-native products, rather than bolting AI onto an existing product as a feature.
• Comfortable working fully remote, across time zones, on a small and highly autonomous team.