Software Engineer, AI Systems

🔥 13 hours ago

🇨🇦 Canada – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 AI Engineer

👻 Ghost score 22%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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AI Fund

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2017

💼 Consulting

🏥 Healthcare

🏭 Manufacturing

Consulting • Healthcare • Manufacturing

AI Fund is a venture studio focused on launching AI-based companies that aim to drive progress across various sectors. By partnering with talented founders and tech pioneers, AI Fund supports the development of innovative applications of artificial intelligence, spanning industries such as manufacturing, mental health, education, and more. The organization acts as a minor co-founder, helping to cultivate startups that leverage the transformative potential of AI to improve the world.

📋 Description

• Build and operate multi-step LLM pipelines coordinating model calls, tool calls, graph queries, retrieval, quality gates, and specialist-agent handoffs • Extend Haven’s coordinated agent team and orchestration layer from incident evidence through analysis, review, and enterprise learning • Design the context layer across Neo4j graph traversal, vector search, and hybrid retrieval • Build evaluation datasets, scoring systems, regression suites, model comparisons, human-label loops, and per-stage quality attribution • Implement tracing, tool-call audits, cost and latency monitoring, failure handling, and quality dashboards • Detect loops, hallucinations, and silent model drift before customers do • Select models across OpenAI, Anthropic, and Google based on task requirements • Partner with product and knowledge engineering and help shape the AI roadmap • Report to the CTO and contribute across multiple founding-team responsibilities

🎯 Requirements

• AI or ML engineering experience, including shipping LLM systems that real users depend on • Hands-on experience building and debugging multi-step, tool-calling workflows with LangGraph, LangChain, or an equivalent framework • Repeatable approach to LLM evaluation, including representative datasets, regression testing, LLM-as-judge techniques, or human review loops • Experience assembling context for LLMs and judgment about what to retrieve, how much, and why • Track record of owning systems from deployment through monitoring and incident response • Experience diagnosing and fixing a production failure or regression • Comfort working across model providers and explaining tradeoffs in quality, latency, cost, context, and operational risk • Comfort with Neo4j and Cypher, or a comparable graph store, and ability to ramp quickly on graph data modeling; strongly preferred • Strong Python • Production experience with FastAPI, asynchronous services, testing, observability, and maintainable interfaces • Deep graph experience, including Cypher, schema evolution, MERGE patterns, embeddings, and operating a live knowledge graph; nice to have • Enterprise AI security experience; nice to have • Azure and hybrid search experience; nice to have • Experience with Azure AI Search, Pinecone, MongoDB Atlas, pgvector, Elasticsearch, or similar platforms; nice to have • Prior enterprise-level B2B SaaS experience; strongly preferred

🏖️ Benefits

• Small team, high ownership • Direct feedback from safety teams and visible customer impact • Opportunity to work closely with the CTO, product, and knowledge engineering • Consequential technical decision-making and rapid customer impact • Meaningful reasoning problems in a safety-critical domain • Evaluation-first culture focused on measurable, observable, improvable quality