Scalable AI Solutions Architect

4 days ago

Rajahmundry, Andhra Pradesh, India beBeeEngineering Full time ₹ 1,20,00,000 - ₹ 2,00,00,000

About Us

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At ARC-Net, we drive industry-oriented AI research into scalable solutions by bringing together top-tier talent and industry partners to take on projects with industry relevance. Our model enables people working with us to contribute to short and long-term research-oriented industry projects and deliver solutions while building for scale and managing innovation under real constraints.

We have delivered successful projects in space technology and AI-based interview assessment, alongside ongoing research in Climate Tech and MedTech. With several successful projects already completed, we are expanding our portfolio and growing our impact.

About the Role

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As a Senior AI Engineer, you will take ownership of translating research into scalable AI systems. You will design architectures, guide technical decisions, and deliver projects with measurable outcomes. Alongside building solutions, you'll mentor younger engineers and work closely with IISc researchers and industry collaborators to expand our impact.

Key Responsibilities

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  1. Architect and operationalize technical roadmaps for AI projects.
  2. Lead design and development of scalable, industry-relevant AI solutions.
  3. Collaborate with faculty, researchers, and industry partners to define goals, milestones, and deliverables.
  4. Manage project teams by providing technical roadmaps and mentorship to young engineers and researchers who are part of our team.
  5. Contribute to our mission of translating research into solutions with measurable outcomes.

Required Qualifications

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  1. Bachelor's or Master's degree in Computer Science.
  2. Proven 3 years of experience working with R&D focused cross-disciplinary projects.
  3. Proficiency in system architecture, model design, and scalable implementation.
  4. Excellent communication and ability to work in fast-paced, collaborative environments.

Preferred Qualifications

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  1. Experience in translating research into shipped solutions (e.g., prototypes, products, or platforms).
  2. Background in industry–academia collaborations, technology transfer, or original research initiatives.
  3. Familiarity with innovation ecosystems, or applied research labs.
  4. Active connections or participation in the AI, SaaS, or broader tech community.

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