TMS
Qualified, Reliable, Viable
AI Development Engineer – DevX Platform, 13+ years exp.
Artificial IntelligenceArtificial IntelligenceFull TimeRemoteTeam 51-200H1B SponsorCompany SiteLinkedIn
Location
New Jersey
Posted
11 days ago
Salary
Not specified
Bachelor Degree5 yrs expEnglishAWSAzureDockerGoogle Cloud PlatformJava ScriptJenkinsKubernetesMicroservicesNode.jsPythonReactType ScriptVue.jsGo
Job Description
• 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.
Job 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.
Benefits
- All your information will be kept confidential according to EEO guidelines.