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# AI Led Engineering Enterprise AI, Cloud & Platform Transformation (Onsite/Hybrid)

- **Company:** Talent Search Pro
- **Location:** Chicago, IL, United States
- **Experience:** Experienced
- **Salary:** $200,000.0 - $220,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Computing Platforms, Microsoft Azure, Cloud Computing, Cloud Engineering, Continuous Integration, DevOps, Monitoring of Systems, HP Systems Insight Manager, Python (Programming Language), Machine Learning, Performance Tuning, Reliability Engineering, Prometheus, Software Engineering, Systems Integration, Datadog, Data Logging, Google Cloud, GitHub Copilot, System Availability, Large Language Models, AgentCore, Generative AI, Agentic-AI, Kubernetes, Infrastructure Automation Frameworks, Machine Learning Operations, Cloud Migration, Model Context Protocol, Terraform, Splunk, AIOps, Dynatrace, Docker
- **Published:** October 17, 2026
- **Apply:** https://www.thejobnetwork.com/job/3f533f8d-ed8d-48e4-b8db-f7d9ca24b95f/ai-led-engineering-enterprise-ai-cloud-platform-transformation-onsitehybrid

## About the Role

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., * 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.

Relevant Technologies and Technical Skills

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.

## Description

* 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.