Principal AI Engineer (US)

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 mentor's 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.  
-Test, evaluate, and analyze the performance of LLM and other GenAI models.  
- Model routing, orchestration services, evaluation of harnesses, prompt/versioning stores, and telemetry—to accelerate adoption across teams.  
 - Drive cross-functional roadmaps and integration standards across OCIO and business teams—setting API/versioning contracts, optimizing LLM/agent cost performance, and mentoring engineers to raise the bar.  
- Evaluation of leadership establishes offline/online evaluation methodologies for agent behavior and safety, with dashboards tied to business outcomes. 
- 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 
- Coach and hold vendors accountable to our best practices and milestone deliverables 
- 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 
- Perform other tasks and duties as assigned 
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. 
• Proven leadership shipping agentic AI at scale across multiple products, setting organization wide standards for reasoning loops, tool use/function. 
• Must Have - Expertise & Hands-on experience in Agentic AI Tech stack primarily in Microsoft (Foundry, AI Search, Open AI, RAG, CoPilot Studio) and Anthropic (Claude Cowork and Claude Code). 
• Must Have - Advanced Python & Java expertise in production systems (testing, packaging, performance profiling) and deep experience extending agent frameworks such as Anthropic, Lang chain, 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 
• Good understanding of Salesforce Agentforce and Boomi Agentic AI platform capabilities is highly desired