Infrastructure Engineer
Infrastructure Engineer Job Summary: Talent Senior ServiceNow is in search of an Infrastructure Engineer for a contract position in Minnetonka, MN. The opportunity will be ten months with a strong chance for a long-term extension. Position Summary: We are looking for an experienced contractor who is highly proficient in Python and has practical experience developing AI-powered systems. The preferred candidate should have worked with AI agents, Model Context Protocol (MCP), modern data management techniques, and cloud platforms to create scalable, production-ready solutions. Primary Responsibilities/Accountabilities: Design, build, and maintain Python-based services and automation workflows Implement MCP for agent communication, control, and observability Build, transform, and manage data pipelines supporting AI and analytics use cases Deploy, monitor, and optimize solutions in cloud environments Collaborate with product, data, and engineering teams to deliver end-to-end solutions Ensure code quality, performance, security, and maintainability Qualifications: Python: Advanced proficiency; production experience with APIs, async processing, and testing AI / LLM Agents: Experience designing and implementing autonomous or semiautonomous AI agents (e.g., tool-using agents, planners, orchestrators) MCP (Model Context Protocols): Experience with agent communication, coordination frameworks, or protocol-driven AI architectures Data Management: Data modelling and data pipelines Working with SQL and NoSQL databases Experience with data quality, governance, and large‐scale datasets Cloud Experience: Hands-on work in at least one major cloud platform (Azure, AWS, or GCP) Experience with cloud storage, compute, and managed services Familiarity with CI/CD and cloud native deployment patterns Preferred: Experience with vector databases and embeddings Familiarity with MLOps or LLMOps practices Experience with streaming data or event driven architectures Knowledge of security and compliance considerations for AI systems Prior work in enterprise or large-scale data management Healthcare or other data regulated experience preferred Engagement Characteristics Contractor is expected to work independently with minimal supervision Comfortable operating in fast moving, evolving technical environments Strong documentation and communication skills Experience collaborating with remote and cross functional teams Technical Skills AI/LLM Agent and MCP (Model Control Protocols) – Google ADK, Copilot Studio Cloud Experience – Google Cloud or Azure preferred. Database Knowledge – BigQuery, Firestore, Cloud SQL, etc. Data pipeline – Dataflow Power Automate Automation Tooling – UI Path, etc. CI/CD Pipeline – Azure DevOps Pipeline Infrastructure as Code (IaC) - Terraform Role 2: Infrastructure Engineer (Terraform, CI/CD, GCP & Azure, Data & AI Platforms) Position Summary: We are looking for an experienced Infrastructure Engineer to design, automate, and operate scalable cloud infrastructure supporting data platforms and AI/ML workloads across GCP and Azure. This role focuses on Infrastructure such as Code, CI/CD automation, cloud networking, and enabling reliable, secure environments for data engineering and analytics teams. Primary Responsibilities/Accountabilities: Design, provision, and manage cloud infrastructure using Terraform Build and maintain CI/CD pipelines using Azure DevOps Provision and manage GCP infrastructure, including compute, storage, IAM, and networking Support and manage Azure infrastructure (VNets, networking, compute, storage) Design and implement network provisioning (VPC/VNet architecture, routing, firewalls, load balancers, private connectivity) Build and operate infrastructure for data platforms (data lakes, warehouses, streaming, analytics platforms) Provision and support AI/ML infrastructure, including GPU resources and AI platforms Implement security best practices, IAM, encryption, and compliance controls Optimize infrastructure for performance, reliability, and cost Collaborate with data engineering, analytics, and ML teams Document infrastructure, architecture, standards, and operational runbooks Qualifications: Strong experience with Terraform (Infrastructure as Code) Experience with CI/CD pipelines, preferably Azure DevOps Strong hands-on experience with Google Cloud Platform (GCP) Solid understanding of cloud networking and network provisioning Experience supporting data platforms or large-scale data workloads Experience with AI/ML infrastructure Strong Linux and scripting skills (Bash, Python, etc.) Preferred: Hands-on experience with Azure infrastructure Experience with Kubernetes (GKE / AKS) Experience with data services such as BigQuery, Dataflow, Dataproc, Synapse, ADLS, Snowflake Monitoring and observability tools (Prometheus, Grafana, Cloud Monitoring) Multi-cloud experience and relevant certifications If this job is a match for your background, we would be honoured to receive your application! 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