Principal AI Solutions Architect

Principal AI Solutions Architect, Healthcare & Life Sciences - USLocation: Dallas / New York / OrlandoResponsibilitiesLead ideation and scoping of AI/ML proof of concepts (PoCs) in coordination with client account leadersRapidly prototype and iterate AI features (chatbots, NLP services, recommender systems, etc.)Direct internal DataArt teams to execute PoCs with clarity, velocity, and alignmentOwn the "show-and-tell" lifecycle: internal demo → stakeholder validation → external client presentationDevelop GenAI applications based on RAG variations, Agentic, hybrid models. Leverage Agentic SDLC and advocate for adoption. Develop with hyperscaler AI tools (Azure, GCP, AWS), LLM APIs, vector search, GenAI, Agentic SDKs and Agentic Runtimes (Agent Core, Agent Engine, etc.)Define reusable AI building blocks and Healthcare-specific agent scaffolds that feed into the Connect AI ecosystemBuild working solutions integrated with cloud data platforms like Snowflake and DatabricksEmbed AI into client-facing products or operations (e.g., personalization, crew ops, service automation)Shape internal best practices for GenAI use in SDLC and Healthcare product lifecycle — from opportunity discovery to ops telemetryCreate AI demo assets: notebooks, dashboards, blog content, or walkthrough videosRun workshops and working sessions with client teams and business leadersAct as a translator and evangelist, helping stakeholders understand responsible AI adoption and potential ROIRequirementsHands-on experience with AI services from at least one major cloud provider (Azure, AWS, GCP)Demonstrated ability to operate at Director level or above in client engagements, influencing both technical and business stakeholdersExperience with designing and implementing RAG based applicationsStrong background with Snowflake and/or Databricks for data engineering and AI pipelinesProven success leading client-facing PoCs or MVPs from inception to deliveryPrior exposure to Healthcare or Life Sciences sectorStrong understanding of Healthcare and/or Life Sciences workflows, regulatory frameworks (HIPAA, CMS-0057-F, GDPR, ISO 13485, ISO 42001, etc.), and industry challenges.Ability to translate fuzzy business goals into AI-enabled outcomes, structuring initiatives from ambiguous needs into scoped, testable, and scalable componentsFluency in evaluating tradeoffs between open-source LLMs and commercial APIs, and designing cost-efficient, scalable architecturesStrong communicator comfortable with both technical teams and business stakeholdersAbility to travel to client site (US, EU)Nice to haveExposure to healthcare data standards (FHIR, HL7) and integrations (eRx, Clearinghouses, TEFCA).Knowledge of GenAI fine-tuning, vector DBs, or orchestration frameworks (LangChain, Semantic Kernel, etc.)Experience developing internal enablement materials or technical contentAwareness of responsible AI practices (e.g., model fairness, explainability, usage boundaries)