JOB SUMMARYClient Fixed Income Institutional Lending Technology team is seeking two highly experienced Applied AI Engineers to design, build, and operate an enterprise-grade GenAI workflow platform. This platform will enhance document data extraction, embed productivity assistants, and automate business workflows across various business lines. This is a hands-on role focused on production systems, not research or demos, requiring deep understanding of GenAI failure modes, evaluation, and governance. The engineers will contribute to reusable GenAI workflows, develop robust AI-based document ingestion and data extraction capabilities with human-in-the-loop review, build agentic AI-powered assistants, and deliver automated content generation. They will also provide expert architectural advice on GenAI, establish LLMOps practices, and implement controls for data handling in a regulated environment, with a explicit path to platform ownership and defining shared GenAI standards.Key Responsibilities
- Design and evolve reusable GenAI workflows used across Lending business lines.
- Develop an enterprise grade AI-based document ingestion and data extraction capability, including traceability, confidence scoring, and human-in-the-loop review.
- Build AI-powered assistants embedded in Lending systems using agentic workflows.
- Deliver automated content and deck generation workflows for reporting and approvals.
- Provide expert advice on GenAI architecture including model selection, orchestration patterns, and evaluation strategy.
- Establish LLMOps practices: extraction accuracy, assistant reliability, prompts management, and audit monitoring.
- Design and implement controls for entitlements, PII handling within open-source models in a regulated environment.Required Qualifications




- 5+ years of strong front-to-back engineering experience (Python or Java), focusing on AI ML platforms and workflows.
- Recent dedicated experience in practical application of GenAI solutions in an enterprise environment.
- Designing and operating GenAI orchestration frameworks in production (e.G., LangChain systems), beyond vendor examples.
- Proven experience building and operating production grade GenAI / LLM platforms, applying patterns such as RAG, tool/function calling, agentic workflows, and validated structured outputs.
- Strong LLMOps expertise, including evaluation harnesses, prompt and version management, regression testing, observability, and reliability measurement in production systems.
- Hands on experience building AI-first data ingestion pipelines with measurable quality, accuracy, and reliability.
- Advanced retrieval experience, including advanced vector search, multi vector and late interaction approaches (e.G., ColBERT, chunking), multi stage retrieval pipelines, metadata filtering, re ranking.
- Solid understanding of evaluation metrics (e.G., recall vs precision, latency vs quality, MRR, NDCG) and how they shape practical RAG system design.
- Experience operating GenAI systems through real production failures (model regressions, retrieval degradation, prompt drift, data quality issues) and designing mitigation strategies.
- Day 1 onboarding onsite / in-office presence required 3x/week in Montreal.Preferred Qualifications
- Fixed Income or Institutional Lending domain experience.
- Experience working in regulated environments with strong audit and control requirements.
- Familiarity with enterprise security, data governance, and entitlement models.
- Experience designing reusable internal platforms or shared developer tooling.
- Frontend experience (Angular or React). #J-18808-Ljbffr

📌 Genai Platform Engineer – Production Ai & Llmops (Montreal)
🏢 Compunnel
📍 Montreal