Description

Key Responsibilities 

• Design, develop, and deploy enterprise Generative AI solutions leveraging AWS Bedrock and Anthropic Claude models.  
• Build advanced conversational AI, summarization, document intelligence, and knowledge retrieval solutions using Claude APIs and Bedrock-hosted foundation models.  
• Develop and optimize Retrieval-Augmented Generation (RAG) architectures using embeddings, vector databases, semantic search, and prompt orchestration frameworks.  
• Engineer scalable AI and ML workflows within Databricks using Delta Lake, Apache Spark, MLflow, and Lakehouse architectures.  
• Develop prompt engineering strategies, AI guardrails, context management, and response evaluation frameworks for enterprise AI applications.  
• Integrate structured and unstructured clinical, research, regulatory, and commercial datasets into AI-driven solutions.  
• Build APIs and microservices to operationalize AI capabilities across enterprise applications and workflows.  
• Implement MLOps and LLMOps best practices for model deployment, monitoring, governance, observability, and lifecycle management.  
• Collaborate with cybersecurity and governance teams to ensure secure, compliant, and responsible AI adoption aligned with HIPAA, GxP, and enterprise data governance standards.  
• Optimize AI workloads for performance, scalability, resiliency, and cost efficiency within AWS cloud environments.  
• Contribute to enterprise AI architecture standards, reusable AI frameworks, and innovation initiatives.  

Required Qualifications 

• Bachelor’s or master’s degree in computer science, Data Science, Engineering, or related discipline.  
• 8+ years of experience in software engineering, AI engineering, machine learning, or cloud data platforms.  
• Strong hands-on experience with AWS Bedrock and Anthropic Claude models in enterprise environments.  
• Experience building GenAI applications using Claude for conversational AI, intelligent document processing, summarization, and enterprise search use cases.  
• Expertise with prompt engineering, prompt chaining, context window optimization, and RAG implementation patterns.  
• Experience with Databricks Lakehouse Platform, Delta Lake, Apache Spark, and MLflow.  
• Strong programming skills in Python and experience with LangChain, LlamaIndex, or similar AI orchestration frameworks.  
• Experience integrating vector databases and semantic search technologies.  
• Strong understanding of AWS-native cloud architectures and AI services.  
• Experience with REST APIs, microservices, CI/CD pipelines, containerization, and infrastructure automation.  
• Familiarity with AI governance, security controls, and responsible AI practices.  
• Experience working in regulated industries such as healthcare, life sciences, or pharmaceuticals preferred.  

Preferred Skills 

• Experience with clinical, genomics, pharmaceutical, or regulatory datasets.  
• Knowledge of AI agent frameworks and autonomous workflow orchestration.  
• Experience implementing secure enterprise AI solutions with guardrails and model evaluation frameworks.  
• Familiarity with Snowflake, Redshift, or cloud data modernization initiatives.  
• AWS Certifications and/or Databricks certifications preferred.  

Technical Environment 

• AWS Bedrock  
• Anthropic Claude  
• Databricks Lakehouse Platform  
• Python / PySpark  
• MLflow  
• LangChain / LlamaIndex  
• Vector Databases  
• Delta Lake  
• AWS Lambda, ECS, EKS, S3, SageMaker  
• GitHub, Terraform, CI/CD Pipelines  
• REST APIs & Microservices  

Success Criteria 

• Deliver secure and scalable enterprise AI solutions leveraging Claude and AWS Bedrock.  
• Accelerate adoption of Generative AI capabilities across research, clinical, and business operations.  
• Establish reusable AI engineering frameworks and LLMOps standards.  
• Improve data accessibility, operational efficiency, and AI governance maturity across the enterprise

Key Skills

Education

Bachelor's or Master's degrees