For over 40 years, LGI has built software that healthcare organizations depend on. AI is now at the heart of that work, not as a destination, but as the engine behind our next generation of mission-critical solutions and our enduring mission: helping healthcare organizations perform at their best. The Solutions Architect designs the end-to-end architecture required to deploy and operate our solutions successfully in each client’s production environment. This includes infrastructure, cloud and hybrid platforms, integrations, systems, networks, databases, security, observability, and site reliability engineering (SRE). During the bid and pre‑sales stages, the Solutions Architect defines the target architecture and technical requirements, evaluates total cost of ownership (TCO), and partners with Sales to develop the Statement of Work (SOW). During implementation and operation, they guide technical delivery and remain accountable for the solution’s availability, performance, scalability, and reliability. This is a hands‑on position for someone who is equally comfortable making high‑impact architecture decisions and investigating traces, query plans, or network traffic during a production incident. As the technical authority and ultimate escalation point for solution architecture, this person works closely with clients, Support, Monitoring, DevOps, SRE, Product Architecture, and R&D.; The position reports to the Customer Delivery & Performance Engineering group. They believe real‑world feedback is one of the fastest ways to improve quality. Bilingualism in French and English is mandatory , as the position involves working with technical documentation and communicating with French
- and English‑speaking clients, partners, and colleagues.



Design the client‑specific production architecture across infrastructure, cloud and hybrid platforms, systems, networks, integrations, databases, security, and observability. Size and optimize environments for availability, performance, scalability, resilience, and cost, using Infrastructure as Code and automation wherever appropriate. Support bids and pre‑sales engagements by defining technical requirements, developing the target architecture, evaluating TCO, and partnering with Sales on the SOW. Resolve the most complex production issues by reproducing failures, identifying root causes, and implementing durable improvements to performance and reliability. Lead the technical response to high‑severity incidents, from diagnosis and mitigation through verified resolution and follow‑up corrective actions. Build prototypes, load tests, failure reproductions, and diagnostic tools to validate assumptions and settle technical questions with evidence. Design and optimize database architecture, including performance, integrity, capacity planning, and secure schema migrations. Strengthen application observability through logs, metrics, traces, alerts, and dashboards developed with Monitoring, DevOps, SRE, and R&D.; Design and automate CI/CD pipelines and deployment tooling to enable secure, repeatable, and reliable production releases. Monitor production health through reliability and performance indicators,



and assess delivery effectiveness using DORA metrics such as deployment frequency, lead time for changes, change failure rate, and time to restore service. Translate production findings into prioritised technical requirements for R&D;, improving the product’s performance, reliability, observability, and deployability. Embed security, privacy, and regulatory compliance into every architecture decision, particularly where health data is involved. Establish client architecture standards, guide deployment, DevOps, and SRE specialists, mentor technical colleagues, and influence cross‑functional decisions without relying on formal authority. Partner with the AI Lab to define and promote the responsible integration of AI and generative AI—including LLMs, retrieval‑augmented generation, and orchestrated workflows—into client solutions and their supporting architecture. Design AI‑enabled operational capabilities such as anomaly detection, performance analysis, and intelligent automation, with appropriate security, privacy, governance, and human oversight. Help technical teams use AI responsibly and effectively, critically assess AI‑generated outputs, monitor emerging developments, and advise leadership on relevant opportunities and risks. A university degree in computer science, software engineering, or a related discipline, or equivalent qualified experience. Demonstrated expertise in cloud and hybrid architecture, Infrastructure as Code, networking, and client‑specific infrastructure design. Strong knowledge of SRE, high availability, disaster recovery, observability, performance engineering, and incident management. Fluency with diagnostic tools and techniques such as profilers, distributed tracing, packet capture, query plans, load testing,

📌 .NET SOLUTIONS ARCHITECT_Remote (Montreal)
🏢 LGI Healthcare Solutions Santé
📍 Montreal