About this role
AI Solutions Developer - (GenAI / OpenAI)
Financial Crimes Technology (FCT)
Location: Montreal, QC
Role Overview
:We are looking for a hands-on AI Solutions Developer (backend) to help us build AI-enabled capabilities on top of large language models (LLMs) - starting with automated generation of client / customer summaries (e.g., relationship summaries, risk summaries, KYC/CDD profile narratives, and alert/case briefings) from the structured data we already hold. You will integrate OpenAI (and similar) APIs into our backend services, assemble the data and context these models need, design effective prompts, and ship reliable, well-governed features that summarize complex client information into clear, accurate, audit-ready text
.This is a backend / integration role suited to a developer who is comfortable pulling data from multiple sources, calling LLM APIs, shaping the output, and exposing it through services - and who cares about accuracy, safety, and cost in a regulated financial-services environment. We are open to either Java or Python as the primary language
.
Key Responsibilitie
• s:Build AI-enabled features that generate client summaries from structured and unstructured data using OpenAI APIs and similar LLM provider
• s.Integrate LLM calls into application services - prompt construction, model selection, structured outputs (JSON), streaming responses, token-budget and cost management, retries, and error handlin
• g.Assemble context for the model - retrieve and shape data from databases and internal APIs into the structured input the model needs to produce each summary typ
• e.Design and iterate on prompts and templates for different summary "types," and build lightweight evaluation to check accuracy, completeness, and faithfulness (no hallucinated facts
• ).Expose capabilities through clean backend APIs so other teams can consume the
• m.Apply responsible-AI guardrails - PII handling/redaction, prompt-injection defenses, output validation, and audit logging suitable for a regulated environmen
• t.Collaborate with engineering, business analysts, and compliance stakeholders to define what a "good" summary looks like and to validate output
• s.Use AI coding assistants (e.g., GitHub Copilot, ChatGPT) to accelerate your own developmen
t.
Required Qualifications (Must Hav
• e):3-5 years of professional software development experience as a hands-on developer (junior to mid-leve
• l).Strong proficiency in at least one backend language - Java (with Spring Boot) and/or Python (FastAPI / Flask). We are open to eith
• er.Hands-on experience calling LLM APIs - particularly the OpenAI API (chat completions, function/tool calling, structured/JSON outputs, embeddings) - or a strong willingness and demonstrated aptitude to ramp up quick
• ly.Practical prompt-engineering skills - writing, testing, and iterating on prompts to get reliable, well-structured outp
• ut.Experience integrating with data sources - relational databases (SQL) and REST AP
• Is.Solid understanding of RESTful API design and JS
• ON.Good engineering fundamentals - version control (Git), testing, and writing maintainable co
• de.Awareness of data privacy / PII concerns and a careful, quality-focused minds
• et.Strong problem-solving and communication skills; able to work with non-technical stakeholders to shape requiremen
• ts.Bachelor's degree in Computer Science, Engineering, or related field (or equivalent experienc
e).
Familiarity / Nice to Have (any subset is a pl
• us):LLM / orchestration libraries - Spring AI, LangChain / LangChain4j, LlamaIndex, Semantic Kernel, or equival
• ent.Other LLM providers - Anthropic Claude, Google Gemini, or open-source models (Llama, Mistr
• al).Streaming responses (SSE / WebSockets) and async patterns for LLM out
• put.Evaluation tooling for LLM outputs - measuring faithfulness, hallucination, and task success; familiarity with Langfuse / LangSmith or similar observability for
• AI.Cloud experience (Azure / AWS / GCP) and containerization (Dock
• er).CI/CD (Jenkins or similar) and build tooling (Gradle / Maven for Java, or pip/poetry for Pyth
• on).Responsible-AI / model-governance practices in a regulated cont
• ext.Exposure to financial-services, AML/KYC, compliance, or risk doma
ins.