Python Developer

Job description

AgIntel is building the AgIoT Console - a research-grade platform supporting IoT sensor integration, geospatial analytics, precision agriculture, soil carbon modelling, biogeochemical modelling, and farm intelligence workflows across Atlantic Canada.

Our platform combines distributed backend services, geospatial databases, API-driven dashboards, and containerized infrastructure used by researchers, agronomists, and operational stakeholders.

Role Description We are looking for a hands-on Python Engineer / Developer focused on API hardening, backend stability, testing, troubleshooting, and platform integration within the AgIoT Console ecosystem.

The platform currently includes 130+ registered components, 50+ backend endpoint modules, 184 database migrations, and a database-driven datasource registry (EWDL) that developers are expected to become familiar with during the initial onboarding period.

The environment operates through an agile development pipeline with established local development workflows.

Developers can configure local environments, pull container images from the PEIFA registry, clone and contribute to repositories, and work within the PEIFA Git organization using Kanban-based sprint workflows for assigned tasks, bug tracking, testing, and feature improvements.

Development is organized into two-week sprint cycles with structured review, testing, and deployment stages.

The platform contains extensive in-code documentation, markdown-based technical references, architecture guides, workflow documentation, and operational handoff notes to support onboarding and ongoing development activities.

Familiarity with Slack-based team communication, agile collaboration, code reviews, testing pipelines, and production deployment workflows is expected.

Once onboarding and initial ramp-up are completed, developers are expected to contribute production-level code that can be reviewed, validated, and deployed to live console services and production endpoints.

Key Responsibilities

Harden, maintain, and troubleshoot existing REST APIs built using FastAPI, Flask, and WSGI-based services.

Diagnose and fix broken bindings between FastAPI endpoints, EWDL datasource registry services, PostgreSQL/PostGIS data layers, and React dashboard panels.

Troubleshoot issues where APIs return successful responses but UI/data rendering fails due to schema drift, field mismatches, timeout misconfiguration, or datasource mapping problems.

Maintain and validate frontend/backend integration wiring across registered microapps, dashboard components, workflow mappings, and datasource registries.

Perform API validation, regression testing, endpoint verification, and backend QA.

Expand and maintain automated testing coverage using Pytest, Postman, Playwright, and related QA tooling.

Identify platform issues, document findings, raise bug tickets, and track improvements through Kanban sprint workflows.

Work on assigned backend development tasks, fixes, and feature improvements.

Support concurrent API processing, multithreading, load handling, and distributed backend services.

Manage PostgreSQL/PostGIS data workflows, SQL data processing, and backend integrations.

Support Docker/containerized Linux environments, reverse proxies, and deployment workflows.

Work with OAuth2.0, SSO, SSL/TLS security, authentication, and authorization systems.

Assist with admin/user dashboard integrations, workflow routing, and backend connectivity.

Maintain development hygiene by organizing working trees, validating deployment mappings, and ensuring production-ready code quality.

Required Skills

Strong Python 3 experience with modern backend engineering practices including type hints, structured logging, packaging, virtual environments (venv), profiling, and performance optimization.

Experience with FastAPI, Starlette, Flask, REST API architecture, OpenAPI-first workflows, request/response schemas, pagination, versioning, structured error handling, and WSGI/ASGI deployment environments (Uvicorn/Gunicorn).

Familiarity with asynchronous Python development including asyncio, concurrent request handling, connection pooling, scalable API workflows, background task processing, queue workers, Redis-backed workflows, and distributed backend services.

Strong SQL/database experience including PostgreSQL, PostGIS, indexing, EXPLAIN-driven optimization, transactions, geospatial processing, spatial indexes (GiST), migrations, and backend data pipelines.

Hands-on familiarity with GIS/geospatial tooling and workflows including GeoPandas, Shapely, PyProj, Rasterio, Fiona, CRS handling, GeoJSON processing, reprojection, and vector/raster spatial workflows.

Experience working with SQLAlchemy 2.x, Alembic migrations, and combining ORM workflows with performance-oriented raw SQL where required.

Experience with Docker / Docker Compose, multi-stage container builds, image registries, and Linux / WSL-based development environments aligned with production systems.

Familiarity with Nginx reverse proxy patterns, OAuth2/OIDC, SSO, JWT validation, SSL/TLS security, secure headers, rate limiting, and authorization workflows.

Experience with NumPy, Pandas, and backend data processing workflows involving Parquet, Arrow, JSONL, and chunked/streaming large-file processing.

Experience with testing and QA frameworks/tools including Pytest, httpx TestClient, Postman, Playwright, OpenAPI contract validation, regression testing, and structured QA workflows.

Familiarity with Git workflows, pull requests, CI/CD pipelines, agile/Kanban development methodologies, Slack-based collaboration, and staged production deployment pipelines.

Comfortable working within two-week sprint cycles across development, testing, staging, and production deployment environments.

Nice to Have

React/dashboard integration experience.

Familiarity with Material-UI (MUI), Recharts, Plotly, Leaflet, or Mapbox GL.

Experience with Keycloak authentication flows.

Familiarity with EWDL-style datasource registries and API-driven dashboard architectures.

Experience working with production systems and platform stability engineering.

Strong familiarity with Geospatial/GIS platforms and workflows.

Experience working with PostGIS, spatial datasets, geometry processing, mapping layers, geotemporal data, and geospatial API integrations.

Experience working with production systems and platform stability engineering.

Familiarity with AI/ML workflows, LLM-assisted engineering tools, and agent-driven development environments is considered an asset.

How We Work

Dockerized and containerized development workflows.

API-driven architecture with distributed backend services.

Structured testing, validation, and QA-focused workflows.

Strong emphasis on maintainability, reliability, and production hardening.

Logistics Term: May 15, 2026 – September 30, 2026

Hours: ~20 hrs/week

Compensation: Hourly contract, based on experience

Equipment: BYOD laptop; sandbox/test access provided

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Required Skill Profession

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