Applied Ai Engineer

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 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).
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