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- Tasks: Lead AI solutions in healthcare, bridging tech and real-world impact.
- Company: Join a forward-thinking tech company transforming healthcare with AI.
- Benefits: Competitive pay, health insurance, flexible holidays, and a supportive culture.
- Other info: Dynamic role with opportunities for travel and professional growth.
- Why this job: Shape the future of healthcare with innovative AI solutions and real client outcomes.
- Qualifications: Experience in AI services, strong communication skills, and healthcare knowledge.
The predicted salary is between 80000 - 100000 ÂŁ per year.
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. You will shape how AI is adopted across the healthcare and life sciences industries — from intelligent copilots and personalization engines to developer acceleration and operational optimization — by prototyping real solutions, articulating business value, and driving adoption from C‑suite to delivery teams. You will work closely with client account teams (50+ active clients) and DataArt’s AI + Data Lab to identify high‑value use cases, prototype rapidly, validate with stakeholders, and showcase scalable solutions that clients can adopt.
Responsibilities
- 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
Requirements
- 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)
Nice to have
- 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
Benefits
Competitive compensation, health insurance, flexible vacation, and a supportive work environment. Benefits may vary by region and contract type.
Principal AI Solutions Architect, Healthcare & Life Science employer: DataArt Solutions, Inc
Contact Detail:
DataArt Solutions, Inc Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Principal AI Solutions Architect, Healthcare & Life Science
✨Tip Number 1
Network like a pro! Get out there and connect with folks in the healthcare and AI space. Attend industry events, webinars, or even local meetups. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio that highlights your AI projects, especially those related to healthcare. Use platforms like GitHub to showcase your prototypes and solutions. This will give potential employers a taste of what you can do.
✨Tip Number 3
Don’t just apply blindly! Tailor your approach for each role. Research the company and its projects, and during interviews, discuss how your experience aligns with their needs. This shows you’re genuinely interested and not just sending out cookie-cutter applications.
✨Tip Number 4
Apply through our website! We’ve got loads of opportunities waiting for you. Plus, applying directly can sometimes give you a leg up in the hiring process. So, don’t hesitate – get your application in and let’s make some AI magic happen!
We think you need these skills to ace Principal AI Solutions Architect, Healthcare & Life Science
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter for the Principal AI Solutions Architect role. Highlight your experience with AI services and how it relates to healthcare and life sciences. We want to see how you can bridge the gap between tech and real-world impact!
Showcase Your Prototyping Skills: Since prototyping is a big part of this role, include examples of AI features you've developed or worked on. Whether it's chatbots or NLP services, we love seeing your hands-on experience. Let us know how you’ve driven measurable outcomes in past projects!
Communicate Clearly: Your ability to communicate complex ideas to both technical and non-technical stakeholders is crucial. Use clear language in your application to demonstrate this skill. We’re looking for someone who can act as a translator between teams, so show us you can do that!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you don’t miss any important updates. Plus, it shows you’re keen on joining our team at StudySmarter!
How to prepare for a job interview at DataArt Solutions, Inc
✨Know Your AI Tools
Make sure you’re well-versed in the AI services from major cloud providers like Azure, AWS, or GCP. Be ready to discuss how you've used these tools in past projects, especially in healthcare settings, as this will show your hands-on experience and understanding of the industry.
✨Showcase Your Prototyping Skills
Prepare to talk about specific proof of concepts (PoCs) you've led or contributed to. Highlight your ability to rapidly prototype AI features and how you’ve iterated based on stakeholder feedback. This will demonstrate your practical skills and your approach to driving measurable outcomes.
✨Communicate Clearly with Stakeholders
Practice explaining complex AI concepts in simple terms. You’ll need to act as a translator between technical teams and business stakeholders, so being able to articulate the business value of AI solutions is crucial. Think of examples where you’ve successfully done this in the past.
✨Understand Healthcare Regulations
Brush up on relevant healthcare regulations and workflows, such as HIPAA and GDPR. Being knowledgeable about these frameworks will not only help you answer questions confidently but also show that you understand the challenges and responsibilities involved in implementing AI in the healthcare sector.