AI Solution Architect

BioQuest Solutions

Bengaluru

On-site

INR 1,200,000 - 1,500,000

Full time

14 days+

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Job summary

A technology solutions provider in Bengaluru is seeking an experienced AI Solution Architect to lead the AI development team. The ideal candidate will manage the integration of AI models, oversee proofs of concept, and ensure compliance with ethical standards. Applicants should have 4-5 years of experience in AI software development and a BE/BTech in Computer Science or equivalent. Interested candidates can reach out via email.

Qualifications

  • 4-5 years of relevant experience in AI and software development.
  • Experience with automated, manual, and exploratory testing.
  • Proficiency in defining AI architecture and technical roadmaps.

Responsibilities

  • Lead and manage the AI development team.
  • Conduct research on AI models for integration.
  • Develop proofs of concept for AI-driven capabilities.
  • Collaborate with stakeholders on AI initiatives.
  • Drive recruitment and training for the AI team.
  • Define AI architecture and technical roadmap.
  • Establish MLOps practices for AI models.
  • Ensure compliance with data privacy and ethical standards.

Skills

AI model integration
Team leadership
Cloud-based platforms
MLOps practices
Testing experience

Education

BE/ BTech – Computer Science or equivalent

Job description

Educational Qualifications Required BE/ BTech – Computer Science or equivalent

Experience Required 4-5 years

Position Title/ Designation AI Solution Architect Location Bangalore Educational Qualifications Required BE/ BTech – Computer Science or equivalent Experience Required 4-5 years

Responsibilities
  • Lead and manage the AI development team to deliver scalable and production-ready solutions.
  • Conduct research to determine the best AI models and solutions for integration into the company ecosystem and existing AI products.
  • Develop and oversee proofs of concept (PoCs) to validate AI-driven capabilities and business value.
  • Collaborate with stakeholders to align AI initiatives with overall product vision and business strategy.
  • Drive recruitment, onboarding, and continuous training of AI and engineering talent to build a high-performance team aligned with organizational goals.
  • Automated, Manual, Progression/Regression and Exploratory testing experience and deploymentvalidation support.
  • Define the AI architecture and technical roadmap, ensuring seamless integration into cloud-based platforms and existing systems.
  • Own end-to-end lifecycle of AI feature development—from ideation, design, and prototyping to deployment and performance tuning.
  • Establish MLOps practices for continuous training, evaluation, deployment, and monitoring of AI models.
  • Ensure compliance with data privacy regulations, ethical AI practices, and internal security standards.

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