Senior AI Software Architect

4 days ago

Rajahmundry, Andhra Pradesh, India beBeeEngineering Full time ₹ 1,00,00,000 - ₹ 2,00,00,000
Job Opportunity

We are seeking an exceptional engineer to build and lead the development of our AI vision platform.

This is a high-velocity, AI-native role where you'll leverage AI tools to build at unprecedented speed while maintaining enterprise-grade quality and security standards.

Main Responsibilities

  • Create Automated Image Processing Pipelines for image ingestion, preprocessing, and patch generation.
  • Develop Ai Model Integration Layers for seamless integration of object detection and classification models.
  • Design Quality Control Systems for automated validation and review workflows.
  • Build Data Management Platforms for storing and retrieving intelligence data.
  • Develop End-User Interfaces for intelligence dissemination and visualization.
  • Create Scalable Infrastructure using cloud-native architecture handling large-scale data processing.

Technical Requirements

  • 5+ years of experience in software engineering with 2+ years in AI/ML system integration.
  • Proven track record of leading technical teams (2-10 developers).
  • Experience shipping production ML/AI systems at scale.

Ai-Native Development Expertise

  • Expert-level proficiency in leveraging Ai coding tools.
  • Demonstrated ability to use Ai assistants for rapid prototyping, code generation, and debugging.
  • Experience with Ai-powered testing, documentation, and deployment tools.

Core Technical Skills

  • Backend Development: Python, Node.js, or Go for high-performance systems.
  • Computer Vision Integration: Experience with OpenCV and ML model deployment.
  • Database Systems: PostgreSQL, MongoDB, or similar for geospatial and metadata storage.
  • Cloud Platforms: AWS, GCP, or Azure with container orchestration.
  • Api Development: RESTful and GraphQL APIs for system integration.
  • DevOps: CI/CD pipelines, infrastructure as code, monitoring systems.

You will thrive in fast-paced environments, understand the entire stack from data ingestion to user interfaces, architect systems that are both performant and maintainable, balance speed of development with code quality and security, and make technical decisions with incomplete information.

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