Sr. AI Engineer (AI Platform / SRE)

Insight Global
Miami, FL, United States
3 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
3 years minimum
Working hours
Regular working hours
Job source

Tech stack

LangGraph Framework Artificial Intelligence User Authentication Microsoft Azure Cloud Computing Cloud Engineering Code Generation Code Review DevOps Distributed Systems Github NoSQL
+15 more
Software Architecture Redis Reliability Engineering Software Engineering AI Infrastructure Data Logging Multi-Agent Systems AI Coding Agents Agentic-AI Event Driven Architecture AI Platforms Kubernetes Terraform Serverless Computing Docker

Job description

Seeking a Senior AI Engineer to support and expand an internally developed AI platform used for incident triage, code review, observability, monitoring, and engineering productivity. This role is focused on AI infrastructure, platform engineering, Kubernetes, cloud architecture, and enabling enterprise-wide adoption of agentic AI capabilities.

The team is building and scaling a multi-agent platform that supports engineering teams across the organization. This position will help solve authentication, governance, scalability, onboarding, and AI infrastructure challenges as adoption continues to grow.

Day-to-Day

Support and expand the internal AI platform and agent ecosystem

Develop and enhance AI agents used for incident triage, monitoring, observability, and operational automation

Support Kubernetes-based AI workloads and cloud-native services

Solve authentication, scalability, governance, and platform engineering challenges

Build infrastructure supporting onboarding of new teams and AI use cases

Improve cost attribution, platform reporting, and usage visibility across AI services

Partner with engineering teams adopting agentic AI capabilities

Improve platform reliability, observability, monitoring, and automation

Establish standards and best practices for enterprise AI platform adoption

Requirements

10+ years of software engineering experience across design, development, deployment, and support

10+ years reviewing code and technical solutions against business and operational requirements

5+ years of Terraform and Infrastructure as Code experience

5+ years designing and supporting CI/CD pipelines (Azure DevOps, GitHub Actions, etc.)

5+ years working with observability platforms including logging, monitoring, tracing, dashboards, alerting, and SLOs

5+ years of relational and NoSQL database experience

3+ years of Docker and Kubernetes experience

Experience using AI coding tools and agentic workflows

Strong software architecture and distributed systems background

Ability to evaluate, validate, and improve AI-generated code and infrastructure

Strong cloud-native engineering experience

Experience supporting platform engineering, DevOps, SRE, or cloud infrastructure environments

Experience translating business requirements into technical solutions

Strong testing and validation experience Experience building and deploying agentic AI solutions in production

LangGraph

LangChain

Azure AI Foundry

Platform Engineering experience

SRE experience

Event-driven architecture experience

Advanced Redis experience

Legacy modernization experience

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