AI Developer
- Montreal, QC, Canada
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Job details
- Job type
- Contract
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- Experience
- 3-5 years of professional software development experience as a hands-on developer (junior to mid-level).
- Posting language
- English
- Posted
Original job description
Job Title: AI Developer
Location: Montreal, QC
Job Description:
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.
- Bachelor's degree in Computer Science, Engineering, or related field (or equivalent experience).
More about this job
Responsibilities
Build and integrate LLM-powered client-summary features, including prompt design, context assembly, structured outputs, API delivery, and cost and error management. Implement responsible-AI safeguards and lightweight output evaluations, and collaborate with engineering, business, and compliance stakeholders to define and validate summary quality.
Requirements
Requires 3–5 years of hands-on software development experience and proficiency in Java with Spring Boot and/or Python with FastAPI or Flask, along with experience or aptitude in using LLM APIs and practical prompt engineering. Candidates should also have experience with SQL and REST APIs, strong software engineering fundamentals, awareness of privacy and PII concerns, effective communication skills, and a bachelor's degree in a related field or equivalent experience.
Skills
- Java
- Spring Boot
- Python
- FastAPI
- Flask
- OpenAI API
- Prompt Engineering
- LLM Integration
- SQL
- REST API Design
- JSON
- Git
- Software Testing
- Data Privacy
- PII Handling
- Backend Development
Visa sponsorship
Not detected in the job text
Categories
- Technology
- Software
- Data & Analytics
Keywords
- Artificial Intelligence
- Large Language Models
- OpenAI API
- Chat Completions
- Function Calling
- Tool Calling
- Structured Outputs
- JSON
- Embeddings
- Prompt Engineering
- Java
- Spring Boot
- Python
- FastAPI
- Flask
- SQL
- Relational Databases
- REST APIs
- Backend APIs
- Git
- Software Testing
- Token-Budget Management
- Cost Management
- Streaming Responses
- Output Validation
- Prompt-Injection Defense
- PII Redaction
- Audit Logging
- Responsible AI
- Client Summaries