Ascendion - Generative AI Architect

Job Summary :

Ascendion is seeking an accomplished and visionary GenAI Architect with over 12 years of experience to lead the architectural design and strategic implementation of Generative AI solutions, specifically within the Healthcare IT domain. Based onsite in Hyderabad or Chennai, this pivotal role will involve driving end-to-end AI solutioning, ensuring alignment with critical business objectives, technical standards, and stringent healthcare compliance requirements, including HIPAA. You will be a key driver of innovation, bridging the gap between advanced AI capabilities and practical, secure applications that transform healthcare End-to-End AI Solutioning & Architecture : Lead the complete architectural design and blueprinting of Generative AI solutions for complex Healthcare IT projects, from conceptualization to deployment and Strategic Alignment : Define and align AI / ML strategies and roadmaps with overarching business objectives, ensuring technical solutions meet strategic goals and adhere to enterprise architectural standards.

• Secure & Compliant Design : Design highly scalable, resilient, and secure AI solutions with a deep focus on healthcare-specific compliance requirements, particularly HIPAA regulations, ensuring data privacy and security.
• Cross-Functional Collaboration : Serve as a key technical leader and collaborator, working closely with cross-functional teams including data scientists, machine learning engineers, software developers, product managers, and business stakeholders to drive successful project delivery.
• Hands-on Development & Framework Expertise : Maintain hands-on proficiency with leading AI / ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) and core programming languages (Python, Java, Scala) to guide development and perform Cloud Platform Specialization : Leverage extensive experience with cloud platforms for AI / ML deployments, with preferred expertise in Google Cloud Platform (GCP) and its suite of AI services (e.g., Vertex AI, Dialogflow, BigQuery ML).
• Innovation & Adoption : Drive the exploration, evaluation, and adoption of emerging AI technologies, leading proof-of-concepts (POCs) and fostering a culture of continuous innovation within the team.
• MLOps Leadership : Champion and implement robust MLOps practices, designing and overseeing the automation of the entire machine learning lifecycle, from data ingestion and model training to deployment, monitoring, and retraining.
• Technical Leadership & Mentorship : Mentor junior and mid-level engineers and architects, lead technical discussions, facilitate architectural reviews, and effectively communicate complex technical concepts to both technical and non-technical audiences.
• Industry Expertise : Apply deep knowledge of healthcare standards, regulatory requirements, industry needs, and best practices to inform architectural decisions and solution Qualifications :
• Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related quantitative field.
• 12+ years of progressive experience in software development and enterprise architecture, with a significant and demonstrable focus on Artificial Intelligence and Machine Learning solutions.
• Proven track record in architecting and delivering large-scale, complex AI / ML systems in a production environment.
• Strong hands-on experience with core AI / ML frameworks such as TensorFlow, PyTorch, and Scikit-learn.
• Exceptional programming skills in Python, Java, and / or Scala.
• Solid understanding of cloud-native architectures and experience deploying AI solutions on at least one major cloud platform (AWS, Azure, GCP).
• Demonstrated experience with MLOps principles and tools for automating the ML lifecycle.
• Excellent communication, presentation, and interpersonal skills, with the ability to influence stakeholders at all Expertise :
• Deep knowledge of Google Cloud Platform (GCP) and its comprehensive suite of AI / ML services (e.g., Vertex AI, BigQuery ML, Dataflow, Cloud Functions, Pub / Sub).
• Extensive experience in the Healthcare IT domain, including familiarity with industry standards, data interoperability (e.g., FHIR), and regulatory compliance (e.g., HIPAA).
• Prior experience in architecting and implementing Generative AI solutions (LLMs, Diffusion Models) for real-world applications.
• Experience with containerization (Docker, Kubernetes) and microservices architecture.
• Certifications in cloud architecture (e.g., Google Cloud Certified - Professional Cloud Architect) or AI / ML.

ref : hirist.tech)