What are the responsibilities and job description for the Forward Deployed AI Engineers (FDEs) - R01563547 position at Brillio?
Role Brief:
We are looking for Forward Deployed AI Engineers (FDEs) to partner with one of the largest healthcare payers in the U.S. to redefine business processes using AI and agentic workflows.
This role goes beyond traditional engineering. You will work directly with business and technology teams to design, build, and deploy AI agents that transform how healthcare operations function, while enabling teams to become AI-native and self-sufficient.
You will operate at the intersection of AI, engineering, and healthcare operations, delivering real-world impact across critical payer workflows.
• Reimagine and redesign healthcare processes using AI-first principles
• Identify opportunities to replace or augment manual workflows with AI agents
• Partner with business stakeholders to translate problems into working AI solutions
• Design, build, and deploy AI agents for enterprise workflows
• Implement multi-agent systems using LLMs (prompting, memory, tool usage)
• Rapidly prototype and productionize solutions using platforms such as: OpenAI, Anthropic, Google (Gemini)
• Embed with client teams (business IT) to Whiteboard solutions
• Build prototypes in days/weeks
• Deploy and iterate rapidly
• Operate as a trusted advisor builder, not just a developer
• Leverage AI across the full software lifecycle: Code generation and refactoring, Automated testing and validation, Documentation and observability
• Drive productivity improvements across engineering teams
• Train business and ops teams to use AI tools and agents effectively, build and iterate workflows independently, develop reusable playbooks and frameworks
• You will work on transforming core healthcare processes such as: Claims Processing & Adjudication, Automate intake, validation, and exception handling
• Prior Authorization - AI-driven clinical review, decision support, and workflow orchestration
• Member & Provider Contact Center - Intelligent agents for call routing, resolution, and digital containment
• Provider Data Management - Data intake, validation, and directory accuracy
• Care Management & Utilization Review - AI-assisted case management and risk identification
• Revenue Cycle & Payment Integrity - Fraud, waste, and abuse detection using AI
• Identify opportunities to replace or augment manual workflows with AI agents
• Partner with business stakeholders to translate problems into working AI solutions
• Design, build, and deploy AI agents for enterprise workflows
• Implement multi-agent systems using LLMs (prompting, memory, tool usage)
• Rapidly prototype and productionize solutions using platforms such as: OpenAI, Anthropic, Google (Gemini)
• Embed with client teams (business IT) to Whiteboard solutions
• Build prototypes in days/weeks
• Deploy and iterate rapidly
• Operate as a trusted advisor builder, not just a developer
• Leverage AI across the full software lifecycle: Code generation and refactoring, Automated testing and validation, Documentation and observability
• Drive productivity improvements across engineering teams
• Train business and ops teams to use AI tools and agents effectively, build and iterate workflows independently, develop reusable playbooks and frameworks
• You will work on transforming core healthcare processes such as: Claims Processing & Adjudication, Automate intake, validation, and exception handling
• Prior Authorization - AI-driven clinical review, decision support, and workflow orchestration
• Member & Provider Contact Center - Intelligent agents for call routing, resolution, and digital containment
• Provider Data Management - Data intake, validation, and directory accuracy
• Care Management & Utilization Review - AI-assisted case management and risk identification
• Revenue Cycle & Payment Integrity - Fraud, waste, and abuse detection using AI
• 6–12 years of experience in software engineering, AI, or related fields
• Strong software engineering background (Python, APIs, microservices)
• Experience with LLMs, prompt engineering, and AI frameworks
• Familiarity with agent frameworks (LangChain, Semantic Kernel, etc.)
• Cloud experience with Amazon Web Services, Microsoft (Azure)
• Experience building AI/ML or LLM-powered applications
• Understanding of structured unstructured data pipelines
• Knowledge of model evaluation, monitoring, and governance
• Ability to work directly with business stakeholders
• Strong problem-solving and communication skills
• Experience in rapid prototyping and iterative delivery
• Experience in U.S. healthcare payer or PBM environments
• Understanding of claims, prior auth, or care management workflows
• Familiarity with regulatory and compliance considerations (HIPAA, etc.)
• Prior experience in client-facing or consulting roles preferred
• Strong software engineering background (Python, APIs, microservices)
• Experience with LLMs, prompt engineering, and AI frameworks
• Familiarity with agent frameworks (LangChain, Semantic Kernel, etc.)
• Cloud experience with Amazon Web Services, Microsoft (Azure)
• Experience building AI/ML or LLM-powered applications
• Understanding of structured unstructured data pipelines
• Knowledge of model evaluation, monitoring, and governance
• Ability to work directly with business stakeholders
• Strong problem-solving and communication skills
• Experience in rapid prototyping and iterative delivery
• Experience in U.S. healthcare payer or PBM environments
• Understanding of claims, prior auth, or care management workflows
• Familiarity with regulatory and compliance considerations (HIPAA, etc.)
• Prior experience in client-facing or consulting roles preferred
• Work at the forefront of AI-driven enterprise transformation
• Build real-world AI agents that replace traditional workflows
• Operate in a forward-deployed model with direct business impact
• Opportunity to scale from small pods to enterprise-wide transformation programs
• Number of business workflows transformed using AI
• Reduction in manual effort / cost-to-serve
• Adoption of AI tools by business teams
• Speed of prototyping → production deployment
• Reduction in manual effort / cost-to-serve
• Adoption of AI tools by business teams
• Speed of prototyping → production deployment
• Experience with healthcare platforms (claims, CRM, contact center)
• Exposure to tools like Salesforce, ServiceNow, or Epic integrations
• Prior experience with companies like Palantir Technologies or similar forward-deployed models
• Exposure to tools like Salesforce, ServiceNow, or Epic integrations
• Prior experience with companies like Palantir Technologies or similar forward-deployed models