Role Summary :
The AI Solutioning Architect is responsible for designing, leading, and delivering AI-driven solutions aligned with business strategy and technical standards-particularly within the Healthcare IT domain. This role drives the architectural vision for AI / ML initiatives from concept to deployment, ensuring solutions are innovative, scalable, secure, and compliant. The Architect collaborates cross-functionally to translate business needs into robust AI systems, supports strategic planning, and champions AI best practices across the organization.
Key Responsibilities :
Solution Architecture & Strategy :
- Lead AI technical solutioning aligned with business goals and enterprise architecture.
- Define and evolve the AI / ML architectural roadmap using best practices and emerging trends.
- Design end-to-end AI pipelines-data ingestion, modeling, deployment, and monitoring.
Stakeholder Engagement & Delivery :
Collaborate with business leaders to capture requirements and shape AI solutions.Present technical concepts and project updates to both technical and non-technical stakeholders.Lead Proof-of-Concepts (POCs) to validate feasibility and strategic alignment.Execution & Governance :
Provide hands-on technical leadership to data scientists and engineers.Ensure adherence to security, scalability, compliance (e.g., HIPAA), and MLOps practices.Create and maintain solution documentation (architecture diagrams, specs, guidelines).Technology Enablement :
Recommend and leverage AI / ML tools, especially within Google Cloud Platform (GCP).Guide platform selection and technical stack decisions for AI projects.Stay current on AI trends and propose innovative use cases for competitive advantage.Leadership & Collaboration :
Mentor teams to foster a culture of innovation and technical excellence.Required Qualifications :
Bachelor's / Master's in Computer Science, AI, or a related field.12+ years in software development / architecture with deep AI / ML experience.Strong grasp of AI techniques (supervised, unsupervised, reinforcement learning).Expertise in cloud platforms (preferably Google Cloud Platform) and AI tools (e.g., TensorFlow, PyTorch, Scikit-learn).Proven experience building scalable AI systems in Healthcare IT, with regulatory knowledge (e.g., HIPAA).Proficient in Python, Java, or Scala.Strong MLOps understanding for lifecycle automation.Excellent communication, leadership, and stakeholder management skills.Ability to drive technical strategy, lead cross-functional teams, and mentor talent.ref : hirist.tech)
