Senior Platform Engineer

Role overview

Platform and cloud automation

• Develop automated cloud infrastructure provisioning workflows using infrastructure as code tools such as Terraform.
• Create frameworks for deployment, configuration, and management across multiple cloud environments.
• Manage service catalog components and integrate them with platforms such as Backstage.
• Architect and maintain CI/CD pipelines and pipeline code for cloud automation.
• Write Python, Bash, or similar scripts for deployment orchestration.

Generative AI and MLOps

• Apply generative AI models to service catalog capabilities and automation pipeline code quality.
• Build and deploy AI models for AIOps use cases such as anomaly detection and predictive maintenance.
• Deploy RAG workflows using LangChain, Bedrock, Vertex AI, Azure AI, or comparable platforms.
• Construct and fine-tune vector databases and document sources using OpenSearch, Amazon Kendra, or similar tools.
• Prepare and label datasets while maintaining scalability and data integrity.
• Develop agentic workflows and connect generative AI models with operational and AIOps systems.
• Build and maintain MLOps pipelines, assess model performance, track model decay, and optimize systems.

Required qualifications

• Bachelor’s or master’s degree in computer science, engineering, or a related discipline.
• At least 5 years of experience in cloud infrastructure automation, scripting, and DevOps.
• Experience with infrastructure as code tools including Terraform, CloudFormation, or comparable technologies.
• Strong command of Python, cloud AI frameworks such as LangChain, and generative AI workflow design.
• Experience building and deploying RAG or transformer-based AI models.
• Experience constructing vector databases and document sources using OpenSearch, Amazon Kendra, or similar tools.
• Ability to prepare and label AI datasets while optimizing data inputs.
• Familiarity with AWS, Google Cloud, Azure, or another comparable cloud platform.
• Ability to implement MLOps pipelines and track AI system performance.

Nice-to-have qualifications

• Familiarity with agentic architectures and flow engineering.
• Experience using Bedrock Agents or LangGraph to build workflows.
• Understanding of generative AI integration into legacy or complex operational environments.