AI Solutions Engineer
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Job Description
AI Solutions Engineer building full-stack AI applications for healthcare clients at Brillio, an enterprise digital technology services company. Translating healthcare workflows into rapid, governed AI prototypes.
Responsibilities:
- Engage with business stakeholders, VPs, clinical leads, and operations owners to identify high-value problems and translate them into AI opportunities
- Define minimum viable AI solutions, map processes, identify opportunities to reduce friction and cost, and accelerate decisions
- Create scoping documents, ROI estimates, and success criteria
- Design and build AI prototypes within days using Claude and modern AI development tools
- Develop full-stack AI applications involving LLM orchestration, RAG, agentic workflows, REST API integrations, and lightweight front-end interfaces
- Own technical architecture from prompt design through data pipeline and user interface
- Iterate using real user feedback and drive prototypes toward production-grade quality
- Use Claude for code generation, testing, documentation, and solution design
- Partner with the AI Governance team to validate and harden prototypes for enterprise deployment
- Apply responsible AI practices including bias review, explainability, HIPAA compliance, audit logging, and model monitoring
- Document solutions for handoff, scaling, and maintenance
- Contribute reusable patterns to Brillio's AI accelerator library
- Participate in sprint reviews, program steering committees, executive updates, live demos, and client business rhythm meetings
- Communicate technical concepts to non-technical leaders and surface blockers, dependencies, and risks
- Develop deep expertise in client workflows, data, competitive pressures, and regulatory environments
- Build trusted-advisor relationships with healthcare business counterparts
- Share client engagement learnings with Brillio's applied AI community
Requirements:
- 8+ years of healthcare industry experience, specifically direct hands-on experience in health insurance operations or health system clinical and operational workflows
- Demonstrated use of the Claude API as a development tool, including prompt engineering, tool use, and agentic patterns
- Full-stack AI engineering capability, including LLM integration, RAG, agentic orchestration, REST API development, and lightweight front-end interfaces
- Proven ability to move from a business conversation to a working AI prototype within days
- Ability to explain technical solutions, costs, and next steps clearly to healthcare executives without jargon
- Comfort participating in steering committees, executive briefings, and business rhythm meetings
- Ability to structure ambiguous business problems into scoped AI opportunities with clear inputs, outputs, and success criteria
- Ability to build credible ROI and impact measurement business cases
- Strong preference: hands-on experience with LangChain, LangGraph, CrewAI, AutoGen, or equivalent frameworks
- Strong preference: familiarity with HL7, FHIR, ICD-10, CPT, claims data structures, HIPAA, CMS regulations, and FDA digital health guidance
- Strong preference: forward-deployed, embedded, consulting, or startup engineering experience
- Strong preference: experience shipping AI in a health insurance technology company or health system
- Strong preference: experience contributing to reusable AI platforms or accelerators
- Strong preference: knowledge of AI governance, responsible AI, model risk management, bias evaluation, audit logging, and enterprise AI governance frameworks
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