Vrinda International
AI PLATFORM ENGINEER
Bangalore, INVor OrtVertragVollzeit
Veröffentlicht am 10. Sept. 2026
Diese Stelle wird in EN ausgeschrieben
WE ARE HIRING | AI PLATFORM ENGINEER
Location: Bangalore
Experience: 6–8 Years
Work Mode: On-Site
CTC: ₹15–17 LPA
ROLE OVERVIEW
We are looking for an experienced AI Platform Engineer to build and support production-grade AI/LLM platforms, orchestration workflows, automation, and CI/CD pipelines.
KEY RESPONSIBILITIES
- Design, develop, and maintain production-grade AI/LLM platform solutions
- Build and manage LLM orchestration workflows and agent-based systems
- Implement Agent Loops, State Machines, and ReAct patterns
- Develop and maintain CI/CD pipelines for AI applications and platform deployments
- Automate deployment, environments, security, and platform operations
- Design and implement REST/OpenAPI-based APIs
- Establish prompt versioning, testing, evaluation, and optimization practices
- Collaborate with engineering and DevSecOps teams to deliver scalable and reliable AI solutions
REQUIRED SKILLS
- Strong hands-on experience with Python for production-grade applications
- Experience with LLM orchestration frameworks such as LangGraph, LangChain, Bedrock, or Cortex
- Strong understanding of Agent Loops, State Machines, and ReAct patterns
- Experience with Prompt Engineering, versioning, testing, and evaluation
- Hands-on experience with CI/CD; GitLab CI/CD highly preferred
- Experience with GitLab pipelines, runners, deployment, environments, security, and automation
- Strong understanding of DevSecOps practices
- Experience in API design and development using REST/OpenAPI
- Strong software engineering and troubleshooting skills
Rollenübersicht
Jobart
Vollzeit
Erforderliche Kompetenzen
Python (production-grade application development)LLM Orchestration Frameworks (LangChain, LangGraph, Bedrock, Cortex)Agent Loops design and implementationState Machine design for orchestrationsReAct pattern implementationPrompt Engineering, versioning, testing and evaluationCI/CD for AI applications (GitLab CI/CD)GitLab pipelines, runners, deployment and environment automationDevSecOps practices (security-integrated DevOps)REST/OpenAPI API design and developmentDeployment and infrastructure automationProduction-grade AI/LLM platform development and maintenanceSoftware engineering and troubleshootingCross-team collaboration with engineering and DevSecOps teams
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