AI Product Engineer

Remote, USA
Posted Jun 13, 2026
Full-time

This is a remote position.
Job Description – AI Product Engineer  
Experience – 7+yrs 
Location: Remote 
Timings: 5:30 PM – 2:30 AM IST 
Notice Period: Immediate Joiners Only 
Role Overview 

We are looking for a highly driven AI Product Engineer who thrives in fast-paced execution environments and can rapidly build, iterate, and launch AI-powered products. This role requires a hands-on builder mindset with strong ownership, urgency, and the ability to convert ideas into production-ready solutions quickly. 

Key Responsibilities 

Build and deploy AI-powered applications using Google Cloud Vertex AI and Python.  

Rapidly prototype and ship features using modern “vibe coding” and AI-assisted development workflows.  

Design, develop, and manage scalable REST APIs and backend integrations.  

Implement and manage integrations with Stripe, OAuth, and third-party services.  

Collaborate with stakeholders to translate business requirements into technical solutions.  

Take ownership of end-to-end product delivery, from development to deployment.  

Optimize applications for scalability, reliability, and performance.  

Continuously iterate based on product feedback and evolving requirements.  

Required Skills & Experience 

Strong engineering experience with Google Cloud Vertex AI.  

Proficiency in Python for backend and AI application development.  

Proven experience in rapid prototyping and AI-assisted/vibe coding workflows.  

Deep expertise in:  

REST API development  

Stripe integrations  

OAuth authentication systems  

Full-stack integrations  

Strong understanding of product management and business alignment.  

Demonstrated ability to independently own projects and ship production-ready code quickly.  

Excellent problem-solving and debugging skills.  

Strong verbal and written communication skills.  

Preferred Qualifications 

Experience working in startup or high-velocity product environments.  

Familiarity with cloud-native architectures and deployment workflows.  

Exposure to AI product lifecycle management and LLM-based applications.

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