TMS

Qualified, Reliable, Viable

AI Development Engineer – DevX Platform, 13+ years exp.

Artificial IntelligenceArtificial IntelligenceFull TimeRemoteTeam 51-200H1B SponsorCompany SiteLinkedIn

Location

New Jersey

Posted

13 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.

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