We are seeking an experienced Principal AI Platform Engineer / AI & Cloud Platform Architect to lead the design, engineering, and operation of enterprise-scale AI platforms. This role combines AI engineering, enterprise platform architecture, cloud transformation, Site Reliability Engineering (SRE), and production operations.
The ideal candidate brings extensive experience across AI, DevOps, cloud engineering, platform engineering, and AIOps/observability. The role requires hands-on Python development, experience deploying AI/ML solutions in production, and the ability to design secure, scalable, and reliable platforms for mission-critical or regulated environments.
Design, build, and maintain enterprise-scale AI platforms and cloud infrastructure.
Develop and integrate AI solutions using Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and AI agents.
Implement and operate AIOps and observability platforms to monitor system performance, reliability, and operational health.
Lead cloud transformation initiatives across AWS, Azure, and/or Google Cloud Platform (GCP).
Support production AI/ML environments, including model deployment, monitoring, lifecycle management, and optimization.
Develop infrastructure automation, CI/CD pipelines, and platform engineering capabilities.
Implement scalable infrastructure using technologies such as Kubernetes, Docker, Terraform, and service meshes.
Integrate AI development tools and engineering copilots into software engineering workflows.
Collaborate with architecture, operations, security, and delivery teams to ensure platform reliability, security, and scalability.
Establish engineering standards and operational practices for mission-critical and regulated platforms.
Minimum of 12 years of experience across AI, DevOps, cloud engineering, SRE, or platform engineering.
Minimum of 3 years of hands-on experience with AI technologies and AI engineering stacks.
Minimum of 5 years of experience designing enterprise platforms.
Minimum of 3 years of experience implementing AIOps or observability platforms.
Mandatory hands-on Python programming experience.
Experience with enterprise cloud transformation initiatives.
Experience supporting production AI/ML environments.
Experience designing or operating mission-critical or regulated platforms.
Strong collaboration and coordination skills across architecture, operations, security, and delivery teams.
AI and Machine Learning
Generative AI and Large Language Models (LLMs)
Retrieval-Augmented Generation (RAG)
AI agents, AgentCore, and Model Context Protocol (MCP)
AWS Bedrock and Amazon SageMaker
Vector databases
Model deployment and lifecycle management
Engineering copilots such as Kiro and GitHub Copilot
Cloud and Platform Engineering
AWS, Microsoft Azure, and/or Google Cloud Platform (GCP)
Infrastructure as Code and automation using Terraform
CI/CD pipelines
Kubernetes and Docker
Service meshes
Enterprise platform architecture and cloud modernization
AIOps, SRE, and Observability
AIOps platform implementation
Infrastructure and application monitoring
Distributed tracing, logging, and metrics
Datadog, Dynatrace, Splunk, Prometheus, and OpenTelemetry
Production reliability, incident analysis, and performance optimization
Note: Candidates are not required to have experience with every named technology. Assessment should focus on transferable technical capabilities, relevant platform experience, and demonstrated implementation of AIOps or observability solutions.
Senior-level engineer or architect with a strong combination of AI engineering, enterprise platforms, and cloud operations experience.
Hands-on Python developer with practical experience building or integrating AI solutions.
Proven track record designing enterprise platforms and supporting production AI/ML workloads.
Demonstrated experience implementing AIOps or observability platforms.
Experience with at least one major cloud provider.
Able to coordinate effectively across technical architecture, security, operations, and delivery teams.
Comfortable evaluating and adopting relevant technologies without requiring experience with every product listed.
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