AI engineer
Listed on 2026-08-05
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IT/Tech
Cloud Computing: Infrastructure & Operations, Systems Engineer, AI Engineer (Applied/Software)
Job Title
Lead development of back-end services, primarily in Python
Work regularly with AI model APIs (such as the Azure OpenAI API or Google VertexAI API)
Work daily with Azure and Google Cloud Platform (GCP)
Project-level development of infrastructure using Terraform
Project-level development of CI/CD pipelines using Git Hub Actions
Troubleshooting of issues related to deployments in Kubernetes (Azure Kubernetes Service)
Ensure accurate observability of solutions deployed in AKS using Datadog, Dynatrace or other related observability tools
Ensure we hit SLAs and lead incident management procedures
Document work and solutions appropriately
Engage with other technology, infrastructure, and product teams as necessary to complete tasks
Participate routinely in team on-call rotation and customer support during business hours
Minimum Qualifications , Skills, and Experience4-year degree in a technology related discipline (Computer Science, Computer Engineering, Information Systems, etc.) or equivalent work experience
5+ years of experience with public cloud technologies (Azure or GCP preferred), including demonstrated application development and hosting focus.
5+ years of experience with container technologies (Docker, Kubernetes, Helm)
3+ years of experience with cloud infrastructure automation tools (Terraform)
3+ years of experience with SDLC and working with Agile development teams
Ability to manage large size technical projects, solving related problems and working to tight deadlines while under pressure
Strong interpersonal and communication skills with demonstrated experience leveraging these skills with technical teams and non-technical business units
Desire to learn new technology and grow across different areas of technology
Familiarity with AI-related concepts such as LLMs, Agents, Model Context Protocol (MCP)
Preferred Qualifications , Skills, and ExperienceExperience developing AI-powered features or applications
Demonstrated ability to prioritize own workload with multiple responsibilities and adaptability to changes in those priorities
Experience building Proxies and Gateway services (e.g.: API Gateways)
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