GenAI Platform Engineer – Production AI & LLMOps

JOB SUMMARY
Client 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 clear 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).