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.
- Robust 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 reporting.
- Experience with uv , ruff, pyright, Python packaging, dependency isolation, and multi-container service deployment.
- Exposure to React and TypeScript for occasional full-stack collaboration, while remaining primarily backend/platform focused.

AI-Augmented Development Expectations This role requires disciplined use of AI tools as part of daily engineering work. The engineer should be able to use AI coding agents and GenAI systems to accelerate implementation, research, validation, and documentation while remaining fully accountable for correctness and safety.

The successful candidate will know how to:

- Give AI agents clear, scoped engineering tasks.
- Require agents to inspect existing code, contracts, tests, and architecture before proposing changes.
- Validate AI-generated code with tests, type checks, linting, runtime review, and security judgment.
- Identify when generated code is unsafe, incorrect, over-engineered, noncompliant, or inconsistent with platform boundaries.
- Use AI tools to improve delivery speed without compromising PHI protection, reliability, auditability, maintainability, or user trust.
- Contribute to AI governance patterns, reusable agent instructions, tool ergonomics, and platform standards.

📌 Senior AI Engineer, Agentic Healthcare Platform (Canada)
🏢 TechDoQuest
📍 Canada