Define’s Client enterprise AI strategy and architecture, including platform selection, LLM evaluation, governance model, technical standards, and alignment with Client’s long-term digital and analytics roadmap.
• Lead the assessment and selection of AI platforms, LLMs, vector databases, orchestration layers, and supporting components, ensuring technology recommendations are vendor neutral and based on Client’s use cases, data landscape, regulatory requirements, and scalability needs.
Identify, evaluate, and prioritize business processes, workflows, and functions suitable for AI enablement, providing clear guidance on where AI should and should not be applied based on business value, risk, feasibility, and compliance considerations.
• Design end-to-end solution architectures for approved AI initiatives, including integration
patterns, data flows, model hosting, API interfaces, prompt frameworks, guardrails, and
monitoring approaches.
• Provide hands-on development and technical implementation support on a case-by-case
basis, which may include building prototypes, developing automation scripts, designing
prompts, integrating APIs, or creating reference implementations.
• Collaborate with Client’s engineering, data, security, and product teams to ensure AI
solutions align with enterprise architecture, data governance, privacy/security standards, and compliance requirements (including HIPAA).
• Establish and document AI best practices, including coding patterns, evaluation frameworks,
testing approaches, prompt design standards, and model performance monitoring guidelines.
• Support change management, training, and capability uplift initiatives, helping Client
teams understand how to adopt, scale, and maintain AI solutions across the enterprise.
• Provide ongoing advisory to leadership, offering strategic insights, risk assessments, ROI
analysis, and recommendations related to AI investments, vendor partners, operating models, and organizational structure.
• Participate in Agile ceremonies and cross-functional planning sessions to ensure AI work aligns with product roadmaps, release plans, and enterprise priorities.
• Deliver architectural documentation, solution diagrams, decision logs, and other artifacts
required to support clarity, governance, and sustainable adoption across the organization.
Required Qualifications
15+ years of experience in software development with significant focus on AI architecture and system design
Proven experience designing distributed, scalable, and high-availability systems
Strong hands-on experience with Microsoft Azure
Proficiency in Python
Mandatory healthcare domain experience, preferably in the Payer domain
1–2 years of hands-on GenAI experience, specifically on Azure, with production deployment exposure
Hands-on experience with CI/CD and infrastructure automation, including Azure Pipelines and Bicep
Terraform experience acceptable with readiness to transition to Bicep
Strong communication skills with the ability to explain technical concepts to non-technical stakeholders
