AI solutions architect in healthcare and life sciences

As a Principal AI Solutions Architect within DataArt’s Healthcare & Life Sciences practice, you will bridge the gap between advanced AI tools and real-world business impact. You’ll operate at the intersection of hands-on prototyping, cross-functional collaboration, and stakeholder education. Your focus: drive measurable client outcomes through AI-enabled efficiencies and new digital experiences.

• Lead ideation and scoping of AI/ML proof of concepts (PoCs) in coordination with client account leaders
• Rapidly prototype and iterate AI features (chatbots, NLP services, recommender systems, etc.)
• Direct internal DataArt teams to execute PoCs with clarity, velocity, and alignment
• Own the "show-and-tell" lifecycle: internal demo → stakeholder validation → external client presentation
• Develop 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 ecosystem
• Build working solutions integrated with cloud data platforms like Snowflake and Databricks
• Embed 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 telemetry
• Create AI demo assets: notebooks, dashboards, blog content, or walkthrough videos
• Run workshops and working sessions with client teams and business leaders
• Act as a translator and evangelist, helping stakeholders understand responsible AI adoption and potential ROI

• Hands-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 stakeholders
• Experience with designing and implementing RAG based applications
• Strong background with Snowflake and/or Databricks for data engineering and AI pipelines
• Proven success leading client-facing PoCs or MVPs from inception to delivery
• Prior exposure to Healthcare or Life Sciences sector
• Strong 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 components
• Fluency in evaluating tradeoffs between open-source LLMs and commercial APIs, and designing cost-efficient, scalable architectures
• Strong communicator comfortable with both technical teams and business stakeholders
• Ability to travel to client site (US, EU)
• Будет плюсом: Exposure 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 content; Awareness of responsible AI practices

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