Principal Product Engineer

Role Overview
# Principal Product Engineer
Experience - 8+Years
Location - Bengaluru,

kindly revert with your updated CV at email ID - clive.lobo@qualitykiosk.com

We are looking for a Principal Product Engineer to take technical ownership across two core products:
An AI Evaluation Platform focused on evaluating, scoring, and analyzing GenAI systems
An AI Test Execution Platform focused on running, managing, and reporting AI-driven test workflows at scale
This role requires strong software engineering fundamentals combined with applied AI understanding. You will design and build production-grade systems where AI models, evaluation logic, and engineering reliability intersect.
This is a hands-on senior individual contributor role, responsible for architecture, critical implementations, and technical decision-making across both products. You will work closely with ML engineers, AI QA teams, and platform engineers to ensure the products are scalable, extensible, and fit for real-world enterprise use
.

Key Responsibilities
Own technical architecture and design for core product components
Build and evolve backend systems supporting:
AI evaluation workflows
Test generation, scoring, and reporting pipelines
Internal dashboards and APIs
Translate product requirements into scalable, maintainable implementations
Collaborate with:
ML engineers on model and evaluation integration
AI QA teams on testability and reliability
Platform/DevOps on deployment and observability
Review code, set engineering standards, and mentor engineers by example
Balance speed vs correctness in an early-stage product environment

Must-Have Skills & Experience
8–12+ years of professional software engineering experience
Strong backend engineering experience (Python preferred; Java/Go acceptable)
Proven experience designing and building production-grade systems
Strong understanding of:
APIs and service-oriented architectures
Data modeling and system scalability
Experience working closely with product managers or owning product requirements

Good-to-Have
Experience building platforms or frameworks (not just applications)
Exposure to AI/ML or GenAI systems (RAG, evaluation, inference pipelines)
Experience in startups or early product teams
Familiarity with cloud-native development