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Québec, QC, Canada
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What you’ll do & how you’ll make your mark
Design & scale async REST/WebSocket APIs with Python 3.11+ + FastAPI, using dependency-injection, type hints, and clean vertical-slice architecture.
Implement multi-agent workflows with Semantic Kernel (handoff, sequential, concurrent) to route traffic among specialised LLM agents.
Integrate LLM providers (OpenAI GPT-4.1/mini, Google Gemini 2.5 Flash) behind a provider-agnostic layer for A/B and cost-aware routing.
Deliver Retrieval-Augmented Generation with vector stores such as Azure AI Search, pgvector, or Chroma.
Expose tool-using agents via OpenAI Assistants (Code-Interpreter) for data-analysis / file-manipulation tasks.
Evolve schemas with SQLModel / SQLAlchemy 2 & Alembic; tune Postgres for high-concurrency async access.
Maintain robust CI/CD (Bitbucket Jenkins) that lint, type-check, test, package (Docker), and deploy.
Instrument services with structlog JSON logs, OpenTelemetry traces, and cost/latency metrics; hold p95 < 100 ms.
Champion AI-assisted development (GitHub Copilot, Cursor) and share pragmatic problem-solving practices with the team.
Who you are & what you’ll need to succeed.
5 + yrs building production APIs in Python; 2 + yrs with FastAPI (or similar async stack).
Deep knowledge of async I/O, Pydantic v2, DI, and observability.
Hands-on with Semantic Kernel or comparable agent frameworks.
Practical RAG implementations using Azure AI Search, pgvector, or Chroma.
Strong Postgres skills, including SQLModel/SQLAlchemy 2 and Alembic migrations.
Proven integrations or Side Projects with LLM APIs (OpenAI, Gemini) and structured-output design.
Dependency management via Poetry and virtual-env isolation.
End-to-end CI/CD ownership (build → scan → test → deploy).
Excellent analytical and problem-solving ability.
Remote work readiness with daily overlap of at least 09:00 – 13:00 EST.
Nice to have
Event/message queues (RabbitMQ, Azure Service Bus, Kafka).
Observability stacks (Grafana, LangFuse) for LLM cost governance
Any Graduate
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