Role Overview
We are seeking a highly experienced and visionary AI / Generative AI Solution Architect to lead the design, development, and implementation of enterprise-scale AI solutions for healthcare and pharmaceutical clients. The ideal candidate will possess strong expertise in Generative AI, Large Language Models (LLMs), cloud AI platforms, MLOps, and healthcare interoperability standards.
In this role, you will be responsible for architecting scalable and secure AI ecosystems that support clinical workflows, healthcare analytics, medical research, and intelligent automation initiatives. You will work closely with engineering teams, data scientists, product stakeholders, and healthcare domain experts to deliver innovative AI-powered solutions while ensuring regulatory compliance, responsible AI practices, and enterprise-grade performance.
This is a strategic and hands-on technical role requiring deep knowledge of AI architecture, RAG pipelines, LLM orchestration, model optimization, and healthcare data systems.
Key Responsibilities
- Architect and deliver end-to-end AI/ML and Generative AI solutions aligned with healthcare and pharmaceutical business requirements.
- Design and implement advanced Retrieval-Augmented Generation (RAG) pipelines using vector databases and LLM orchestration frameworks.
- Develop scalable AI systems for clinical summarization, medical coding assistance, document intelligence, conversational AI, and healthcare automation use cases.
- Build, deploy, optimize, and monitor model training and inference pipelines using AWS Bedrock, SageMaker, Azure OpenAI, or Vertex AI.
- Integrate AI solutions with enterprise healthcare platforms such as Epic EMR, FHIR APIs, HL7 systems, and other healthcare interoperability standards.
- Establish robust MLOps practices including CI/CD for ML pipelines, model versioning, observability, monitoring, and drift detection.
- Define architecture standards, technical roadmaps, and best practices for scalable AI platform adoption.
- Lead technical workshops, solution discovery sessions, and client discussions to gather requirements and define implementation strategies.
- Collaborate with cross-functional teams including Data Engineering, DevOps, Security, Compliance, and Product Management teams.
- Ensure AI systems meet HIPAA, healthcare security, privacy, and responsible AI compliance requirements.
- Implement responsible AI frameworks including explainability, fairness, bias detection, governance, and auditability.
- Create and maintain technical documentation, architecture diagrams, and Architecture Decision Records (ADRs).
- Evaluate emerging AI technologies, frameworks, and tooling to drive innovation and continuous improvement.
Required Skills & Experience
- 8+ years of experience in AI/ML engineering with at least 3+ years in Solution Architecture or Technical Leadership roles.
- Strong hands-on expertise in Generative AI, LLM applications, and Retrieval-Augmented Generation (RAG) architectures.
- Experience with vector databases such as Pinecone, OpenSearch, pgvector, or similar technologies.
- Deep understanding of prompt engineering, fine-tuning strategies, embedding models, and LLM evaluation frameworks.
- Hands-on experience with cloud AI platforms including AWS Bedrock, SageMaker, Azure OpenAI, or Google Vertex AI.
- Strong experience in designing scalable MLOps pipelines and production-grade ML systems.
- Expertise in Python and modern AI/ML frameworks including PyTorch, TensorFlow, HuggingFace, LangChain, and LlamaIndex.
- Experience with containerization and orchestration tools such as Docker and Kubernetes.
- Strong understanding of API integrations, microservices architecture, and distributed systems.
- Experience implementing secure and scalable AI systems in enterprise cloud environments.
Healthcare Domain Expertise (Preferred)
- Experience working with healthcare or pharmaceutical organizations.
- Understanding of healthcare interoperability standards such as FHIR and HL7.
- Exposure to clinical NLP, medical coding (ICD/HCC), patient data processing, or healthcare analytics solutions.
- Familiarity with HIPAA compliance, healthcare security standards, and regulatory requirements.
Core Technologies
- Python, PyTorch, TensorFlow
- LangChain, LlamaIndex, HuggingFace
- AWS Bedrock, SageMaker, MLflow
- Pinecone, OpenSearch, pgvector
- Docker, Kubernetes, CI/CD
- REST APIs, FHIR APIs, Microservices
Soft Skills
- Strong problem-solving and analytical abilities
- Excellent stakeholder communication and presentation skills
- Leadership mindset with the ability to mentor engineering teams
- Ability to work in fast-paced, innovation-driven environments
- Strong collaboration and cross-functional coordination skills
