AI Engineer - WFH

About the Company

Avalon Healthcare Solutions specializes in diagnostic intelligence, helping transform how diagnostic testing is managed across the healthcare ecosystem. Its proprietary Diagnostic Insights Platform combines evidence-based policies, curated laboratory networks, and real-time analytics to simplify diagnostic decisions, support innovation, and optimize healthcare investments.

Avalon supports more than 30 health plans and 100 million members nationwide. Its solutions cover routine and genetic testing management, automated adherence, and end-to-end diagnostic support, helping reduce waste, improve clinical outcomes, and make healthcare more affordable.

Avalon is an Equal Opportunity Employer, including veterans and individuals with disabilities.

About the Role

Avalon Healthcare Solutions is seeking an experienced AI Engineer to lead the design, development, and deployment of scalable AI-powered solutions that support business objectives. This senior technical contributor will take ownership of complex AI features from initial concept through production, evaluating models and technical approaches, building reliable pipelines and integrations, and ensuring solutions meet standards for accuracy, performance, security, and responsible use.

The role focuses on generative AI, agentic systems, workflow automation, and enterprise software engineering. You will collaborate with Product, Design, Data, principal engineers, and architects to translate business needs into practical AI applications, contribute to architectural decisions, and support the development of consistent, secure, and maintainable systems.

Alongside hands-on development, you will help strengthen AI capabilities across the organization through mentoring, code and model reviews, technical guidance, and the adoption of effective AI engineering practices.

Key Responsibilities

• Contribute to the technical direction and architecture of AI-enabled solutions, identifying opportunities to apply generative AI and agentic capabilities to measurable business needs.
• Design, develop, and maintain application services using Python, Rust, Node.js/TypeScript, Java, and other suitable technologies.
• Build and operate agentic systems, including multi-step and multi-agent workflows, tool and function calling, Model Context Protocol (MCP) integrations, retrieval-augmented generation (RAG) pipelines, and agent memory and orchestration patterns.
• Apply advanced prompt and context engineering techniques, including system prompts, structured outputs, few-shot examples, prompt chaining, and prompt versioning.
• Map business processes and build workflow automations using orchestration platforms, preferably n8n, integrating AI agents with enterprise systems, APIs, and data sources.
• Establish evaluation and observability practices for AI systems, including evaluation suites, prompt and agent regression testing, guardrails, tracing, and monitoring of output quality, latency, and token costs.
• Participate in code reviews covering application code, prompts, agent configurations, and workflow definitions, identifying defects and opportunities for improvement.
• Develop modular, reusable application components that work with SQL and vector data sources, applying enterprise software design patterns and emerging AI design patterns.
• Create reusable prompt libraries, tool definitions, and workflow templates.
• Evaluate and promote AI-assisted development tools and practices that can reduce delivery time while maintaining quality.
• Apply continuous integration, continuous deployment, automated testing, test-driven development, and evaluation-driven development practices.
• Follow established software development lifecycle (SDLC) procedures and meet functional, architectural, performance, security, audit, quality, and responsible AI requirements.
• Identify opportunities to improve health plan operations through AI and automation, considering business objectives and related technical dependencies.
• Deliver production-ready AI solutions with clear documentation and knowledge transfer for teams responsible for ongoing operation.
• Mentor junior and mid-level engineers, contribute to technical discussions, and encourage continuous learning and improvement across engineering teams.
• Collaborate with cross-functional partners, communicate technical decisions clearly, and provide constructive feedback that supports team development.

**Required Qualific…