AI Infrastructure Engineer
$154,388–$247,020 year
On-siteBoston, Massachusetts, United States
Job Summary
Productionize internal AI prototypes and tools into reliable applications for business users by managing deployment patterns on Vercel, Azure, AWS, and other cloud environments. Build and maintain CI/CD workflows using GitHub Actions, infrastructure-as-code with Terraform or Bicep, and implement monitoring, secrets management, and access controls. Partner with Corporate AI, IT, and Security teams to support UAT, rollouts, and incident response while establishing runbooks and operational standards. Own ongoing maintenance for existing systems, reduce operational toil, and create lifecycle frameworks that ensure internal tools remain secure, observable, and supportable over time.
Required Qualifications
- 4+ years of experience in platform engineering, DevOps, infrastructure engineering, internal tools engineering, automation engineering, software engineering, or a related technical role
- Strong cloud infrastructure experience with Azure, AWS, or GCP
- Experience with infrastructure-as-code concepts and tools such as Terraform, Bicep, Pulumi, CloudFormation, or similar
- Experience building, maintaining, or supporting CI/CD pipelines, especially with GitHub Actions
- Strong understanding of deployment patterns, environments, secrets management, access controls, monitoring, logging, and production support
- Ability to read, understand, maintain, and improve application code in Python, TypeScript, JavaScript, Node.js, or similar languages
- Experience supporting production or production-like systems, including bug fixes, incident response, dependency updates, documentation, and reliability improvements
- Familiarity with AI application concepts such as LLM APIs, prompt engineering, RAG, agents, model evaluation, AI security risks, and responsible AI practices
- Strong ownership mindset, including comfort taking over work others started, bringing order to ambiguity, and making systems more reliable over time
- Strong communication skills and ability to work with technical teams, IT partners, security stakeholders, and internal business users
- Comfort with brownfield engineering, maintenance, support, and operational excellence
- Practical, service-oriented mindset focused on whether internal tools work well for the people depending on them
Desired Qualifications
- Operating applications on Vercel, including configuration, deployments, environment variables, access controls, monitoring, and production support
- Supporting internal tools, enterprise applications, workflow automation, or business-critical internal systems
- Azure infrastructure, identity, networking, application hosting, and security patterns
- Authentication and authorization patterns such as SSO, OAuth/OIDC, Entra ID / Azure AD, RBAC, service principals, and secrets management
- Observability tools, logging platforms, alerting systems, uptime monitoring, incident response, and operational runbooks
- Maintaining applications built with Python, TypeScript, JavaScript, Node.js, React, or similar modern stacks
- Backend services, APIs, integrations, serverless applications, containers, or cloud-hosted web applications
- AI-powered internal tools, LLM applications, RAG workflows, agents, Slackbots, enterprise integrations, or automation platforms
- Integrating with enterprise systems such as Slack, Jira, Confluence/Quip, Microsoft 365, Salesforce, Snowflake, ServiceNow, or similar
- Working in regulated, security-sensitive, or compliance-heavy environments
- Creating engineering standards, templates, checklists, lifecycle models, or production readiness frameworks
- Participating in UAT, release readiness, stakeholder testing, or internal application rollout processes
- Mentoring or enabling other engineers through documentation, templates, examples, or operational best practices
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