Senior AI Engineer

Position Name – Senior AI Engineer, Agentic Healthcare Platform

Type of hiring – Fulltime

Location – Remote Canada

Job Description:

We are seeking a Senior AI Engineer to help build and operate a production-grade healthcare GenAI platform for patient-facing and enterprise conversational experiences. This role will focus on backend AI services, agentic workflows, MCP tool servers, secure clinical data integrations, and AI platform tooling.

The ideal candidate is a strong Python/Backend Engineer with hands‑on GenAI experience who can build reliable agent systems using Google ADK, LLM tool calling, structured outputs, RAG, guardrails, and healthcare‑safe integration patterns. This is not a prompt‑only role; it requires production engineering judgment across security, observability, testing, deployment, PHI protection, and operational ownership.

Primary Responsibilities

• Design, implement, and maintain backend AI services using Python 3.12+, async service patterns, and frameworks such as FastAPI, Google ADK, and FastMCP.
• Develop and operate agentic GenAI workflows using Google ADK 2.x as a primary orchestration framework.
• Build MCP tool servers and domain‑specific tools for healthcare workflows such as care tasks, medications, scheduling, patient profile lookup, clinical record retrieval, and EHR/FHIR‑backed experiences.
• Integrate LLM providers and GenAI toolkits including Google Gemini/Vertex AI, OpenAI, Anthropic, and related orchestration frameworks where appropriate.
• Implement prompt engineering, RAG, structured output validation, tool selection patterns, memory strategies, and AI guardrails to support safe and reliable model behavior.
• Design secure clinical integration boundaries for FHIR, EHR, user profile, scheduling, and other healthcare systems.
• Protect PHI and sensitive credentials through secure JWT/OAuth flows, delegated authorization, token forwarding, encryption, redaction, and audit‑safe logging.
• Leverage cloud services such as Azure App Configuration, Key Vault, Cosmos DB, Event Hubs, Application Insights, and Google Cloud services such as Vertex AI/Gemini and Cloud Run.
• Build observability, telemetry, evaluation, and impact‑reporting capabilities for AI systems and AI‑assisted engineering workflows.
• Author and maintain automated tests using PyTest and support linting, type‑checking, CI/CD, and containerized deployments.
• Collaborate with product, architecture, security, clinical, platform, DevOps, and application teams to deliver safe AI capabilities through well‑defined HTTP/MCP contracts.
• Participate in architecture discussions, code reviews, production support, operational readiness, and incident response.

Required Qualifications

• 7+ Years of professional software development experience.
• Strong production experience with Python, asynchronous programming, backend APIs, and service‑oriented architecture.
• Hands‑on experience building GenAI applications with Google ADK 2.x or similar agent orchestration frameworks.
• Demonstrated understanding of LLM tool calling, multi‑agent workflows, structured outputs, RAG, prompt engineering, and AI safety/guardrail patterns.
• Experience integrating with LLM providers such as Google Gemini/Vertex AI, OpenAI, Anthropic, or equivalent platforms.
• Experience with FastAPI, PyTest, Docker, CI/CD workflows, and containerized production deployments.
• Strong understanding of API security, JWT/OAuth, delegated authorization, secrets management, and secure service‑to‑service communication.
• Ability to design safe integration patterns for healthcare data, clinical systems, or other sensitive regulated environments.
• Experience with cloud‑native services in Azure and/or Google Cloud.
• Strong debugging, testing, and operational problem‑solving skills.
• Ability to work with high ownership in a small, fast‑moving engineering team.
• Strong communication skills and ability to collaborate across engineering, architecture, security, product, and clinical stakeholders.

Preferred Qualifications

• Healthcare domain experience, especially with HIPAA, HL7/FHIR, Epic integrations, patient portals, scheduling, medication, claims, or clinical workflow systems.
• Experience with MCP, FastMCP v3, model‑tool integration, or agent tool‑server architecture.
• Experience with LangGraph, LangChain, PydanticAI, Semantic Kernel, or other orchestration and structured‑output frameworks.
• Familiarity with OpenTelemetry, Application Insights, Kusto, AI evaluation pipelines, or production observability tooling.
• Experience building AI platform tooling, internal developer enablement tools, AI governance automation, code review automation, or AI impact