Senior Software Engineer II

Role overview

Generative AI engineering

• Build agentic automation platforms for virtual field services and technical support.
• Develop generative AI capabilities across the product lifecycle, from design and development through testing, deployment, and production support.
• Create enterprise data assistants and conversational web experiences grounded in internal APIs, databases, documents, and search indexes.
• Build retrieval and orchestration services using RAG, tool calling, and structured outputs.
• Create workflows that turn conversations and documents into tasks and notifications with human approval and audit logging.
• Develop AI-assisted DevOps tools and reusable engineering frameworks.
• Evaluate and monitor production LLMs, improving quality, accuracy, latency, safety, and cost.
• Implement secure authentication, authorization, tenant separation, logging, error handling, retries, and observability.
• Develop prototypes and MVPs and advance successful solutions into scalable production applications.

Customer delivery and collaboration

• Build customer-specific customizations and product extensions using company APIs.
• Support customer deployments and operational data work, including GIS and geospatial data corrections.
• Integrate products with customer and third-party systems and support delivered solutions in production.
• Prepare technical documentation, deployment notes, and product demonstrations.
• Collaborate with product, engineering, data science, security, services, and customer-facing teams; communicate technical trade-offs clearly.

Qualifications

• Bachelor’s or Master’s degree in a relevant field, or equivalent education and relevant experience.
• At least 5 years of professional software engineering experience and hands-on production generative AI or LLM delivery.
• Strong Python and/or Java skills and experience with React, TypeScript, or JavaScript web applications.
• Experience with microservices, REST APIs, multi-tenant applications, asynchronous processing, and cloud deployment.
• Experience with SQL and NoSQL databases, search systems, queues, caching, enterprise software, and third-party integrations.
• Clear communication with technical and non-technical stakeholders.

Additional assets

• Utility, energy, geospatial, or GIS experience is a plus.
• Familiarity with secure enterprise AI, AI observability, LLM evaluation, or taking AI prototypes into scalable production is a plus.

Compensation

• Expected pay range is CAD 114,750–CAD 162,000 per year, including base pay and short-term incentives.

Application

• The posting represents an active opportunity and remains open until filled.