21 days ago
Boston, MA, USA +3 moreMid Level
H1B sponsor
Base Salary
$154k - $247k/yr
Responsibilities
- Own maintenance, support, and operational readiness for internal AI-enabled applications and tools.
- Productionize prototypes and inherited applications by improving deployment configuration, monitoring, error handling, documentation, testing, access controls, and supportability.
- Build and maintain CI/CD workflows, infrastructure-as-code patterns, deployment automation, secrets management, access controls, logging, alerting, and monitoring.
- Support applications across Vercel, Azure, AWS, GCP, and other cloud environments, with a focus on reliable production operations.
- Participate in testing, UAT, rollout, incident response, bug fixing, dependency updates, security patching, and reliability improvements.
- Create runbooks, checklists, lifecycle standards, production-readiness frameworks, and support handoff processes for internal tools.
- Support infrastructure and operations for AI-powered applications using LLMs, agents, RAG workflows, automation frameworks, and enterprise integrations.
- Collaborate with Corporate AI, IT, Enterprise Data, Security, and business stakeholders to improve internal applications and operational practices.
Requirements
- 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; Azure experience is especially helpful.
- Experience with infrastructure-as-code tools such as Terraform, Bicep, Pulumi, or CloudFormation.
- 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, maintain, and improve application code in Python, TypeScript, JavaScript, Node.js, or similar languages.
- Experience supporting production or production-like systems, including incident response, dependency updates, documentation, bug fixes, and reliability improvements.
- Familiarity with LLM APIs, prompt engineering, RAG, agents, model evaluation, AI security risks, and responsible AI practices.
- Preferred experience includes Vercel operations, Azure identity and networking, SSO, OAuth/OIDC, Entra ID/Azure AD, RBAC, service principals, observability, React, backend services, APIs, serverless applications, containers, and enterprise integrations.
- Preferred experience includes Slack, Jira, Confluence/Quip, Microsoft 365, Salesforce, Snowflake, ServiceNow, regulated environments, UAT, rollout processes, engineering standards, and mentoring or enabling other engineers.
Benefits
- Axon offers benefits intended to support employees physically, financially, and emotionally.
- The role includes base pay, bonus, and stock awards as part of total compensation.
- The posting references Axon’s benefits offerings and provides a link for additional benefits details.
Tech Stack
AWSAzureGitHub ActionsGoogle Cloud PlatformJavaScriptNode.jsPythonReactSnowflakeTerraformTypeScriptVercel
Categories
About Axon
Axon builds TASER energy devices, body and in-car cameras, sensors, and a cloud software suite for managing evidence, records, and real-time operations used by law enforcement, public safety agencies, and enterprises. Revenue comes from hardware sales bundled with SaaS subscriptions and services across its Axon Evidence and Records platforms. Founded in 1993 and headquartered in Scottsdale, Arizona, Axon Enterprise is a NASDAQ-listed public company serving police departments and government customers globally.