Staff Software Development Engineer - Applied AI
New
J
JobgetherSoftware Engineering, AI
CanadaFull-TimeStaff
Salary180,000 - 200,000 CAD per year
Apply NowOpens the employer's application page
Job Details
- Experience
- 7+ years of professional software engineering experience
- Required Skills
- PythonKubernetesAzureCI/CDLLM
Requirements
- 7+ years of professional software engineering experience with a strong track record of designing and delivering production systems.
- 1.5+ years of experience building and operating LLM-based or agentic AI systems in SaaS or enterprise environments.
- Proven experience owning services end to end, including application development, infrastructure as code, CI/CD, monitoring, and production support.
- Strong knowledge of agentic AI technologies, including stateful agent orchestration frameworks, MCP integrations, and AI evaluation or observability platforms.
- Experience designing retrieval-augmented generation (RAG) systems using vector-enabled databases or similar technologies.
- Ability to evaluate model selection strategies, balancing performance, cost, and business requirements.
- Strong Python development skills with solid software engineering fundamentals.
- Experience applying software architecture principles such as Domain-Driven Design and Clean Architecture.
- Familiarity with cloud-native architectures, preferably within Azure environments, including serverless functions, Kubernetes, and event-driven systems.
- Knowledge of AI security practices, including access controls, data protection, prompt injection mitigation, and responsible AI implementation.
- Strong communication skills with the ability to explain complex technical trade-offs and business impacts.
- A proactive mindset with the ability to build new systems, challenge assumptions, and continuously improve engineering practices.
Responsibilities
- Own the architecture, implementation, deployment, and ongoing operation of AI-powered services from concept through production.
- Design data representation layers that provide accurate, efficient business context for large language models and AI agents.
- Build evaluation pipelines to measure AI quality, detect regressions, and monitor production performance.
- Implement security controls and guardrails to prevent prompt injection, unauthorized access, data exposure, and misuse of AI capabilities.
- Manage infrastructure requirements, including infrastructure as code, CI/CD pipelines, observability, and cost optimization.
- Integrate AI services with existing products and APIs through secure interfaces and modern integration patterns.
- Lead and review agent-based software development workflows, improving engineering productivity while maintaining quality and compliance standards.
- Support the evolution of AI development practices, tooling, and automation across engineering teams.
- Make independent architectural decisions and provide technical guidance on complex AI and software engineering challenges.
View Full Description & ApplyYou'll be redirected to the employer's site
