Role: AI Development Engineer - DevX Platform
Duration: Full Time
ABOUT THE DEVX PLATFORM
DevX is next-generation engineering platform designed to accelerate time-to-market and improve code quality through intelligence. It goes beyond simple code completion-DevX orchestrates the entire delivery lifecycle with autonomous agents for
testing smart CI/CD pipelines that self-diagnose failures and automated code review systems that enforce architectural standards.
KEY RESPONSIBILITIES
Platform Core Development: Design and build robust backend services and microservices that power the DevX platform ecosystem.
AI/LLM Integration: Integrate Large Language Models (LLMs) and custom AI models to enable features like semantic code search automated refactoring and natural language infrastructure provisioning.
Offshore Collaboration: 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.
Intelligent Code Analysis: Implement AI-powered static analysis and code generation tools that improve developer productivity and code safety.
Scalable Architecture: Build highly scalable event-driven backend systems using Python or Go to handle concurrent processing of large codebases.
Next-Gen Testing: Design automated testing frameworks where AI agents generate test cases execute regressions and analyze root causes of failures.
Smart CI/CD: Develop integrations for standard CI/CD tools (Jenkins GitHub Actions) that use AI to predict build failures and optimize deployment pipelines.
Observability: Create comprehensive monitoring dashboards to track platform usage model latency and accuracy of AI suggestions.
Technical Strategy: Contribute to the technical roadmap evaluating new AI tools and frameworks to keep DevX at the cutting edge of the industry.
REQUIRED QUALIFICATIONS
Experience: 5-10 years of professional software engineering experience with a focus on backend or full-stack development.
Full-Stack Mastery: Strong proficiency in Python and JavaScript/TypeScript with experience in modern frontend frameworks (React/Vue).
LLM Expertise: Hands-on experience integrating LLM APIs (OpenAI Anthropic AWS Bedrock Azure OpenAI) into production applications.
Platform Engineering: Proven track record of building internal developer platforms SaaS products or complex engineering tools.
API Design: Expertise in designing and implementing RESTful APIs and microservices architectures.
Cloud Native: Proficiency with AWS Azure or GCP including containerization technologies (Docker Kubernetes).
Global Collaboration: Experience working effectively with distributed or offshore engineering teams across time zones.
DevOps Mindset: Strong understanding of CI/CD pipelines infrastructure-as-code and modern DevOps practices.
Education: Bachelor s degree in Computer Science Engineering or equivalent practical experience.
PREFERRED QUALIFICATIONS
Experience with orchestration frameworks like LangChain LlamaIndex or Spec Driven Development.
Knowledge of vector databases (Pinecone Weaviate ChromaDB) and RAG (Retrieval-Augmented Generation) architectures.
Familiarity with the developer tool ecosystem (GitHub API Jira API GitLab) for deep integrations.
Experience with streaming data and real-time processing architectures.
Contributions to open-source AI or developer tooling projects.
Understanding of prompt engineering techniques and LLM fine-tuning strategies.
Role: AI Development Engineer - DevX Platform Duration: Full Time ABOUT THE DEVX PLATFORM DevX is next-generation engineering platform designed to accelerate time-to-market and improve code quality through intelligence. It goes beyond simple code completion-DevX orchestrates the entire delivery lif...
Role: AI Development Engineer - DevX Platform
Duration: Full Time
ABOUT THE DEVX PLATFORM
DevX is next-generation engineering platform designed to accelerate time-to-market and improve code quality through intelligence. It goes beyond simple code completion-DevX orchestrates the entire delivery lifecycle with autonomous agents for
testing smart CI/CD pipelines that self-diagnose failures and automated code review systems that enforce architectural standards.
KEY RESPONSIBILITIES
Platform Core Development: Design and build robust backend services and microservices that power the DevX platform ecosystem.
AI/LLM Integration: Integrate Large Language Models (LLMs) and custom AI models to enable features like semantic code search automated refactoring and natural language infrastructure provisioning.
Offshore Collaboration: 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.
Intelligent Code Analysis: Implement AI-powered static analysis and code generation tools that improve developer productivity and code safety.
Scalable Architecture: Build highly scalable event-driven backend systems using Python or Go to handle concurrent processing of large codebases.
Next-Gen Testing: Design automated testing frameworks where AI agents generate test cases execute regressions and analyze root causes of failures.
Smart CI/CD: Develop integrations for standard CI/CD tools (Jenkins GitHub Actions) that use AI to predict build failures and optimize deployment pipelines.
Observability: Create comprehensive monitoring dashboards to track platform usage model latency and accuracy of AI suggestions.
Technical Strategy: Contribute to the technical roadmap evaluating new AI tools and frameworks to keep DevX at the cutting edge of the industry.
REQUIRED QUALIFICATIONS
Experience: 5-10 years of professional software engineering experience with a focus on backend or full-stack development.
Full-Stack Mastery: Strong proficiency in Python and JavaScript/TypeScript with experience in modern frontend frameworks (React/Vue).
LLM Expertise: Hands-on experience integrating LLM APIs (OpenAI Anthropic AWS Bedrock Azure OpenAI) into production applications.
Platform Engineering: Proven track record of building internal developer platforms SaaS products or complex engineering tools.
API Design: Expertise in designing and implementing RESTful APIs and microservices architectures.
Cloud Native: Proficiency with AWS Azure or GCP including containerization technologies (Docker Kubernetes).
Global Collaboration: Experience working effectively with distributed or offshore engineering teams across time zones.
DevOps Mindset: Strong understanding of CI/CD pipelines infrastructure-as-code and modern DevOps practices.
Education: Bachelor s degree in Computer Science Engineering or equivalent practical experience.
PREFERRED QUALIFICATIONS
Experience with orchestration frameworks like LangChain LlamaIndex or Spec Driven Development.
Knowledge of vector databases (Pinecone Weaviate ChromaDB) and RAG (Retrieval-Augmented Generation) architectures.
Familiarity with the developer tool ecosystem (GitHub API Jira API GitLab) for deep integrations.
Experience with streaming data and real-time processing architectures.
Contributions to open-source AI or developer tooling projects.
Understanding of prompt engineering techniques and LLM fine-tuning strategies.
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