Cloud AI Engineer (RAG Platform)

Requirements

• Software Engineering: 3+ years of Python development, building scalable, production-grade systems using modern Python practices (type hints, uv, Pydantic).
• Cloud & DevOps: 3+ years with AWS (Lambda, Step Functions, IAM, VPC, S3, DynamoDB, API Gateway, CloudFormation/CDK), Docker, CI/CD pipelines (GitLab CI as a plus).
• API Engineering: Proven experience designing and maintaining high-volume, secure RESTful APIs.
• GenAI Foundations: Practical understanding of GenAI concepts including embeddings, vector search, reranking, and hands-on work with RAG/agentic frameworks (LangChain, LlamaIndex).
• Data & Observability: Experience with complex data parsing (e.g. PDFs, unstructured data) and monitoring/observability tools (CloudWatch, Grafana or similar).
• Tooling & Collaboration: Familiarity with AI code assistants (Copilot, Claude Code), strong ownership mindset, proactive problem-solving, and fluent English communication.
• Cross-cloud awareness: Knowledge of similar services in other clouds (e.g. Azure AI Search).

Nice to have

• GxP: Experience in regulated GxP environments.

• Architect & Develop: Design, develop, test, and deploy a scalable and secure RAG (Retrieval Augmented Generation) service using Python and serverless AWS technologies
• Infrastructure as Code: Define and manage all required AWS infrastructure using the AWS Cloud Development Kit (CDK)
• Data Ingestion & Processing: Implement robust pipelines for processing and embedding unstructured data (e.g., PDF, DOCX, HTML), making it ready for semantic search and retrieval
• API Development: Build and maintain a RESTful API for the service
• CI/CD & Automation: Maintain CI/CD pipelines (GitLab CI)
• Monitoring & Optimization: Implement comprehensive monitoring and logging to track service health, performance, and cost. Proactively identify and resolve bottlenecks or issues
• Collaboration: Work closely with our cloud engineering, data science, and AI Platform teams to ensure seamless integration, operational excellence, and alignment with company-wide standards
• Focus on delivering value to business users