- Design, build, and maintain automated CI/CD pipelines using GitHub Actions; implement deployment automation across development, staging, and production environments.
- Support and optimize AWS infrastructure; manage cloud resources, monitoring, and cost optimization.
- Clean up and refactor systems architecture to improve reliability, scalability, and maintainability.
- Triage and resolve infrastructure issues across AI infrastructure, website platforms, and agentic AI tools; prioritize production incidents and system reliability improvements.
- Monitor system health, respond to incidents, and implement fixes in a high-velocity startup environment.
- Maintain runbooks and infrastructure documentation to enable team self-sufficiency.
- Implement basic QA processes and automated testing within CI/CD pipelines.
- Collaborate with AI/ML teams on infrastructure requirements, deployment needs, and tooling support.
- 3-5+ years of professional experience in DevOps, EngOps, or infrastructure engineering roles at startups with demonstrated automation and systems reliability experience.
- Strong proficiency with GitHub Actions for CI/CD pipeline development and automation.
- Proficiency in scripting (Python/Bash) and infrastructure-as-code practices; experience debugging web applications and cloud systems.
- Hands-on experience managing AWS infrastructure (EC2, S3, Lambda, RDS, CloudWatch, etc.) in production environments.
- Experience diagnosing connectivity issues using tools like ping, curl, traceroute, and log analysis
- Comfortable handling large image datasets (e.g., on S3), CSV/JSON files, and performing data quality checks and validation.
- Ability to identify and resolve CPU/memory bottlenecks, slow services, and system performance issues.
- Basic Java and Linux experience
- Bias for action and excellence in maintenance work within scrappy, resource-constrained environments.
- Ability to anticipate downstream issues and handle second-order effects independently without constant oversight.
- Collaborative yet autonomous working style; excited by variety and breadth over narrow specialization.
- Attention to detail in troubleshooting, performance monitoring, and incident documentation.
- Startup background with end-to-end ownership of support across multiple teams.
- Exposure AI/ML infrastructure, model deployment pipelines, or agentic AI tools.
- Exposure to edge AI deployment on NVIDIA Jetson platforms, including running and testing GPU-accelerated workloads (CUDA/TensorRT).
- Experience deploying, running, and troubleshooting containerized (Docker) applications.
Skills Required
- 3-5+ years of professional experience in DevOps, EngOps, or infrastructure engineering roles
- Strong proficiency with GitHub Actions for CI/CD pipeline development
- Proficiency in scripting (Python/Bash) and infrastructure-as-code practices
- Hands-on experience managing AWS infrastructure in production environments
- Experience diagnosing connectivity issues using diagnostic tools
- Basic Java and Linux experience
What We Do
At Precision AI we are on a mission to accelerate artificial intelligence based farming practices to create healthier, happier, and more profitable farms. By leveraging our advanced drones and custom-built AI technology, we can take crop production decisions from a whole field to an individual plant level. This type of decision-making transforms an industry that has been reliant on larger and broader technology for decades. The outcome of our solutions is integrated into the agricultural technology of today and helps craft the machines of tomorrow that will feed the world. Precision AI was founded in 2017 with headquarters in Regina, Saskatchewan. We are scaling rapidly with an elite global team solving the agriculture challenges of farms around the world.








