AI Solutions Developer
Posted on:
2 hours ago
Vacancies:
1 Vacancy
Job Summary
AI Solutions Developer - (GenAI / OpenAI)
Financial Crimes Technology (FCT)
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 Responsibilities:
- Build AI-enabled features that generate client summaries from structured and unstructured data using OpenAI APIs and similar LLM providers.
- Integrate LLM calls into application services - prompt construction model selection structured outputs (JSON) streaming responses token-budget and cost management retries and error handling.
- 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 type.
- 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 them.
- Apply responsible-AI guardrails - PII handling/redaction prompt-injection defenses output validation and audit logging suitable for a regulated environment.
- Collaborate with engineering business analysts and compliance stakeholders to define what a good summary looks like and to validate outputs.
- Use AI coding assistants (e.g. GitHub Copilot ChatGPT) to accelerate your own development.
Required Qualifications (Must Have):
- 3-5 years of professional software development experience as a hands-on developer (junior to mid-level).
- Strong proficiency in at least one backend language - Java (with Spring Boot) and/or Python (FastAPI / Flask). We are open to either.
- 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 quickly.
- Practical prompt-engineering skills - writing testing and iterating on prompts to get reliable well-structured output.
- Experience integrating with data sources - relational databases (SQL) and REST APIs.
- Solid understanding of RESTful API design and JSON.
- Good engineering fundamentals - version control (Git) testing and writing maintainable code.
- Awareness of data privacy / PII concerns and a careful quality-focused mindset.
- Strong problem-solving and communication skills; able to work with non-technical stakeholders to shape requirements.
- Bachelors degree in Computer Science Engineering or related field (or equivalent experience).
Familiarity / Nice to Have (any subset is a plus):
- LLM / orchestration libraries - Spring AI LangChain / LangChain4j LlamaIndex Semantic Kernel or equivalent.
- Other LLM providers - Anthropic Claude Google Gemini or open-source models (Llama Mistral).
- Streaming responses (SSE / WebSockets) and async patterns for LLM output.
- 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 (Docker).
- CI/CD (Jenkins or similar) and build tooling (Gradle / Maven for Java or pip/poetry for Python).
- Responsible-AI / model-governance practices in a regulated context.
- Exposure to financial-services AML/KYC compliance or risk domains.