Embed with product teams to identify business problems suited to AI, build and integrate production AI capabilities, and shape the services roadmap through hands-on engineering and stakeholder collaboration.
Senior AI Architect
📜 Description
- Design and evolve the AI platform, including its agentic runtime, MCP integration layer, model gateway, evaluation, and observability services.
- Guide architectural decisions, design reviews, and technical mentorship for the AI Engineering team.
- Partner with product counterparts to translate roadmaps into architectural requirements and decision documents.
- Create reference architectures, reusable patterns, and templates that help engineering teams build AI agents and MCP servers.
- Establish standards and review processes for security, responsible AI, evaluation, and observability.
🛠️ Requirements
- 12+ years of software engineering and platform architecture experience with deep cloud expertise (Azure preferred), including 5+ years focused on AI/ML infrastructure and GenAI solutions at scale
- Hands-on expertise with agentic systems — agent frameworks, multi-agent orchestration, MCP (Model Context Protocol), tool use, RAG, vector databases, and production LLMOps
- Proven track record designing internal platforms that other engineering teams build on, including developer experience, APIs and SDKs, and self-serve patterns
- Strong architectural breadth across cloud-native systems, distributed systems, data platforms, and security architecture
- Demonstrated ability to produce high-quality architecture documents and decision records, and to communicate design trade-offs clearly to engineering and product audiences
✨ Benefits
- Benefits starting from Day 1
- Retirement plan matching
- Flexible paid time off
- Wellness support programs and resources
- Parental and caregiver leaves
- Fertility and adoption support
- Continuous development support program
- Employee assistance program
Full job description
Team Summary:
The AI Engineering team builds and operates AI Platform — the common foundation every engineering team uses to ship AI capabilities. The team delivers the shared infrastructure, reference patterns, and guardrails that let software engineers across the company build AI agents, MCP servers, and GenAI solutions without reinventing the foundations: model access, orchestration, evaluation, observability, and responsible AI controls. Working in close partnership with product and engineering teams, it turns proven patterns into platform capabilities that compound across the product portfolio.
Job Summary:
The Senior AI Architect is the senior technical leader for PointClickCare’s AI Platform, owning the architecture that enables software engineers across the company to build AI agents, MCP servers, and AI solutions on a common foundation. This role is an enabler, not a product owner: its output is a platform other teams build on, and the patterns, standards, and guardrails that make those teams faster. The Senior AI Architect works closely with product counterparts to review product roadmaps and translate them into architectural designs and decision documents and guides the AI Engineering team in building a robust, scalable agentic platform for the future of PointClickCare.
Key responsibilities:
Design and evolve the architecture of PointClickCare’s AI Platform — the agentic runtime, MCP integration layer, model gateway, and evaluation and observability services that engineering teams build on ensuring it scales with adoption across the product portfolio.
Guide the AI Engineering team through architectural decisions, design reviews, and hands-on technical mentorship, raising the bar for how the platform is designed, built, and operated.
Partner with product counterparts to review product roadmaps, translate upcoming AI capabilities into architectural requirements, and author architecture documents and decision records that de-risk delivery
Enable software engineers across PointClickCare to build AI agents, MCP servers, and solutions on the platform by codifying reference architectures, reusable patterns, and paved-road templates — and by providing direct architectural guidance to consuming teams.
Establish platform standards for security, responsible AI, evaluation, and observability, and run architectural review processes that keep solutions built on the platform consistent, compliant, and production-ready.
Minimum qualifications and Skills:
12+ years of software engineering and platform architecture experience with deep cloud expertise (Azure preferred), including 5+ years focused on AI/ML infrastructure and GenAI solutions at scale
Hands-on expertise with agentic systems — agent frameworks, multi-agent orchestration, MCP (Model Context Protocol), tool use, RAG, vector databases, and production LLMOps
Proven track record designing internal platforms that other engineering teams build on, including developer experience, APIs and SDKs, and self-serve patterns
Strong architectural breadth across cloud-native systems, distributed systems, data platforms, and security architecture
Demonstrated ability to produce high-quality architecture documents and decision records, and to communicate design trade-offs clearly to engineering and product audiences
Preferred qualifications and skills:
Experience with the Azure AI stack (Azure OpenAI, AKS, APIM) and the Databricks lakehouse (Unity Catalog, model serving)
Background in healthcare technology platforms or clinical workflows
Experience guiding engineering teams as a senior architect or technical lead within a platform organization
Expertise in advanced agentic patterns including multi-agent orchestration, tool and MCP server design, agent evaluation, and model fine-tuning pipelines
Deep knowledge of AI governance, responsible AI practices, and model risk management in regulated environments
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