GenAI Technical Architect

1 day ago

Chennai, Tamil Nadu, India Prodapt Solutions Full time ₹ 12,00,000 - ₹ 36,00,000 per year

Overview

Prodapt is looking for a strong backend and platform-focused engineer to join the AI Gateway team. This individual will play a key role in the end-to-end design, development, and deployment of GenAI services built on Google Cloud Platform (GCP), leveraging cloud-native architecture and scalable infrastructure .

This is a high-impact engineering role suited for someone with a strong backend foundation, platform thinking, and a passion for building robust, production-grade GenAI applications.

Responsibilities

  • Lead and contribute to the design, development, and deployment of GenAI applications using Kubernetes (GKE) and modern cloud-native patterns.
  • Build and maintain CI/CD pipelines using tools like Argo CD , GitHub Actions , and infrastructure-as-code practices.
  • Collaborate with ML engineers, infra teams, and product stakeholders to deliver secure, scalable, and observable services .
  • Write clean, maintainable, and efficient code primarily in Python and other backend languages.
  • Support front-end development and integration efforts where needed to ensure smooth end-to-end delivery.
  • Provide technical leadership to a smaller group or squad through code reviews, mentorship, and architecture guidance.
  • Monitor and optimize application health and performance using tools like Splunk and Datadog .

What We're Looking For:

  • Strong proficiency in cloud-native architecture and scaling solutions using GCP and GKE .
  • Experience with CI/CD pipelines , ideally with Argo CD , GitHub Actions, and containerized deployments (Docker, Kubernetes).
  • Proficient in Python and familiar with backend frameworks and patterns.
  • Familiarity with observability and monitoring tools like Splunk, Datadog , or equivalents.
  • Exposure to full-stack development (e.g., React, TypeScript) is a plus.
  • Strong analytical, debugging, and problem-solving skills .
  • Excellent communication and collaboration abilities; ability to work across cross-functional teams.

Bonus Points:

  • Experience working with LLMs or Generative AI frameworks (e.g., LangChain, LlamaIndex).
  • Prior contributions to AI infrastructure, MLOps , or large-scale microservices.
  • Proven ability to lead or mentor junior developers and influence engineering practices.

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