AI summary
The Principal AI Engineer will design and lead AI systems across multiple SaaS solutions, define technical standards, and mentor teams while focusing on AI adoption and delivering business impact.
Eligible from: Unknown
Job Description
PointClickCare is searching for a Principal AI Engineer who will lead and design AI systems across multiple SaaS solutions following our AI Design Patterns, defining technical standards and reusable patterns for reasoning, tool use, and coordinated action. This role will be part of a team which drives enterprise-wide AI enablement by defining strategy, evangelizing adoption, and delivering measurable business impact. It identifies and prioritizes high-value AI use cases, builds scalable AI solutions, and creates playbooks and patterns to accelerate implementation. Through innovation hubs and close collaboration with product, engineering, and operations, the team transforms prototypes into production-ready solutions. Additionally, it invests in talent development, equipping teams with the skills and tools to embed AI across the organization and leads governance of AI solutions across the organization.
To succeed as a Principal AI Engineer at PointClickCare, you need to be highly innovative, creative, accountable, collaborative, and passionate. The Principal AI Engineer partners with cross-functional teams to transition prototypes into secure, observable production solutions and establish playbooks, evaluation frameworks, and platform components to accelerate adoption. Additionally, the Principal AI Engineer mentors' teams and ensures alignment with Responsible AI, security, and regulatory requirements.
Responsibilities
- Set the technical vision and reference architecture for agentic AI across applications defining org-wide standards for reasoning loops, tool use/function calling, memory, safety, and interoperability.
- Build and govern reusable platform components—model broker & multi-model routing, orchestration services, evaluation harnesses, prompt/versioning stores, and telemetry—to accelerate adoption across teams.
- Develop and refine advanced prompting strategies for LLMs.
- Drive cross-functional roadmaps and integration standards across business teams—setting API/versioning contracts, optimizing LLM/agent cost performance, and mentoring engineers to raise the bar.
- Establish and evolve evaluation frameworks for LLMs and agentic systems, including offline and online testing methodologies, safety assessments, quality metrics, and business outcome dashboards.
- Be the go-to Subject Matter Expert (SME) and internal AI expert for relevant enterprise applications, senior leadership, vendors, business partners and internal team members while staying ahead of emerging trends and advising on best practices
- Identify, prioritize and execute AI use cases with clear business outcomes
- Be a coach/mentor for other engineers on AI maturity, including performing peer reviews, leading technical knowledge sharing sessions, establishing engineering best practices, approving pull requests and improving the overall quality of the technical solution
Qualifications we are looking for:
- Proven leadership shipping agentic AI at scale across multiple products, setting organization wide standards for reasoning loops, tool use/function calling, memory, safety, and interoperability.
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Must Have - Expertise & Hands-on experience in Agentic AI Tech stack primarily in Microsoft (Azure AI Foundry, Azure OpenAI, and Azure AI Document Intelligence) and Anthropic (Claude Cowork and Claude Code).
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Must Have - Advanced Python & Java expertise in production systems (testing, packaging, performance profiling) and deep experience extending agent frameworks such as Anthropic, LangChain, and Foundry.
- RAG/agent data pipeline expertise: document preprocessing (OCR/NER), chunking strategies, embeddings, vector stores, and data quality/versioning—with evaluation of harnesses for quality, cost, and latency
- Extensive knowledge and understanding of enabling and maturing AI in a SaaS landscape.
- Model serving and cost/perf optimization: experience with model broker patterns, multi-model routing, and serving stacks
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Must Have - knowledge of relational databases (e.g. Microsoft SQL Server, PostgreSQL)
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Experience using system and performance monitoring tools (e.g. AppDynamics, Kibana, OpenTelemetry)
- BSc/BA in Computer Science or a related degree
Bonus points for:
· Experience with Docker, Kubernetes and Istio
· Experience with AWS/Azure cloud services or equivalent
· Experience with Service Oriented Architecture
· On-call experience with production grade systems#LI-AV1
#LI-Hybrid
About the job
- Posted on
- Sep 2, 2026
- Job type
- Full-time
- Location
- MississaugaHybrid
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