AI Development Engineer – DevX Platform, 13+ years exp.
United States
Full Time
4 hours ago
H1B Sponsor
Key skills
AWSAzureDockerGoogle Cloud PlatformJavaScriptJenkinsKubernetesMicroservicesNode.jsPythonReactTypeScriptVue.jsGoAILLMLarge Language ModelsOpenAIVueGCPGoogle CloudGitHub ActionsBedrockRESTfulGitHubSaaSCI/CD
About this role
Role Overview
Design and build robust backend services and microservices that power the DevX platform ecosystem.
Integrate Large Language Models (LLMs) and custom AI models to enable features like semantic code search, automated refactoring, and natural language infrastructure provisioning.
Act as a technical liaison and co-developer with our India-based engineering team, participating in daily stand-ups and code reviews to ensure architectural alignment.
Implement AI-powered static analysis and code generation tools that improve developer productivity and code safety.
Build highly scalable, event-driven backend systems using Python, Node.js, or Go to handle concurrent processing of large codebases.
Design automated testing frameworks where AI agents generate test cases, execute regressions, and analyze root causes of failures.
Develop integrations for standard CI/CD tools (Jenkins, GitHub Actions) that use AI to predict build failures and optimize deployment pipelines.
Create comprehensive monitoring dashboards to track platform usage, model latency, and accuracy of AI suggestions.
Contribute to the technical roadmap, evaluating new AI tools and frameworks to keep DevX at the cutting edge of the industry.
Requirements
5-10 years of professional software engineering experience with a focus on backend or full-stack development.
Strong proficiency in Python and JavaScript/TypeScript, with experience in modern frontend frameworks (React/Vue).
Hands-on experience integrating LLM APIs (OpenAI, Anthropic, AWS Bedrock, Azure OpenAI) into production applications.
Proven track record of building internal developer platforms, SaaS products, or complex engineering tools.
Expertise in designing and implementing RESTful APIs and microservices architectures.
Proficiency with AWS, Azure, or GCP, including containerization technologies (Docker, Kubernetes).
Experience working effectively with distributed or offshore engineering teams across time zones.
Strong understanding of CI/CD pipelines, infrastructure-as-code, and modern DevOps practices.
Bachelor's degree in Computer Science, Engineering, or equivalent practical experience.
Tech Stack
AWS
Azure
Docker
Google Cloud Platform
JavaScript
Jenkins
Kubernetes
Microservices
Node.js
Python
React
TypeScript
Vue.js
Go
Benefits
All your information will be kept confidential according to EEO guidelines.