Glance AI is an AI commerce platform shaping the next wave of e-commerce with inspiration-led shopping, less about searching for what you want and more about discovering who you could be. Operating in 140 countries, Glance AI transforms every screen into a stage for instant, personal, and joyful discovery, where inspiration becomes something you can explore, feel, and shop in the moment.

Its proprietary models, seamlessly integrated with Google’s most advanced AI platforms, Gemini and Imagen on Vertex AI, deliver hyper-realistic, deeply personal shopping experiences across categories such as fashion, beauty, travel, accessories, home décor, pets, and more. Designed to seamlessly integrate into everyday consumer technology, Glance AI reimagines the future of e-commerce with inspiration-led discovery and shopping.

With an open architecture built for effortless adoption across hardware and software ecosystems, Glance AI is creating a platform that can become a staple in everyday consumer technology. It partners with the world’s leading smartphone makers, connected TV manufacturers, telecom providers, and global brands — meeting people where they are: on mobile, smart TVs, and brand websites.

Through Glance AI’s rich first-party data and unparalleled consumer access, it harnesses InMobi’s global scale, insights, and targeting capabilities to create high-impact, performance-driven shopping journeys for brands worldwide. Part of the InMobi Group, a global technology and advertising leader reaching over 2 billion devices and serving more than 30,000 enterprise brands worldwide, Glance AI is backed by Google, Jio Platforms, and Mithril Capital.

Job Summary

We're looking for a Senior Backend Software Development Engineer (SDE 3) with deep technical expertise in building and operating production systems at scale. You'll own entire components/services within microservices and data pipelines that handle ~200K queries per second and process petabytes of data daily. This role demands hands-on coding excellence, strong Low-Level Design (LLD) skills, and complete ownership—from component architecture through infrastructure management to cost optimization. You'll architect solutions, lead technical decisions, and drive operational excellence while shipping code daily.

Key Responsibilities:

• Component Ownership: Own one or more critical components/services end-to-end—responsible for architecture, development, deployment, operations, and evolution
• Technical Ownership: Own the entire lifecycle of your components—design, implementation, testing, deployment, monitoring, incident response, and continuous improvement
• Low-Level Design: Create detailed technical designs (LLD) for complex systems—defining data models, APIs, concurrency patterns, and failure modes
• Hands-on Development: Write production-grade code daily—this is not a purely architectural role; you'll be deep in the codebase
• Infrastructure Ownership: Own and operate the infrastructure your components run on—capacity planning, scaling, reliability improvements
• Cost Management: Drive cost optimization for owned components—analyze spending, identify waste, implement efficient architectures
• Scale & Performance: Build and optimize systems handling 200K+ QPS and petabyte-scale data processing
• Observability: Design and implement comprehensive monitoring, alerting, and debugging capabilities for owned components
• Incident Leadership: Lead incident response for your components and related services, conduct post-mortems, drive systemic improvements
• On-Call Excellence: Participate in on-call rotations and ensure your components are operationally sound (runbooks, alerts, dashboards)
• Technical Roadmap: Define and drive the technical roadmap for your owned components—balancing feature development, tech debt, and operational improvements
• Technical Mentorship: Guide junior and mid-level engineers on system design, code quality, and production best practices
• Cross-functional Collaboration: Work with product, infra, and other eng teams to define requirements and deliver solutions
• Agile Execution: Break down complex projects, deliver incrementally in daily cadence, iterate based on feedback

Required Qualifications:

• Experience: 4-5+ years building and operating backend systems in production environments at scale
• Education: B.E./B.Tech in Computer Science or equivalent practical experience
• Component Ownership: Proven track record of owning significant components or services from inception to maturity—demonstrable end-to-end ownership
• Low-Level Design (LLD): Proven ability to create detailed technical designs—data structures, algorithms, API contracts, concurrency models, failure handling
• Programming Mastery: Expert-level proficiency in at least one modern language (Go, Python, Java, etc.) with track record of writing maintainable, performant production code
• Databases: Deep hands-on experience with SQL and NoSQL databases—schema design, query optimization, indexing strategies, operational troubleshooting
• Microservices at Scale: Extensive experience building, deploying, and operating microservices handling high throughput and large data volumes
• Data Pipelines: Strong background designing and running data processing pipelines at scale (batch and/or streaming)
• Observability: Expert understanding of metrics, logging, tracing, and alerting—you know how to make systems debuggable
• Production Operations: Significant experience with incident response, on-call rotations, debugging live issues under pressure
• Infrastructure Knowledge: Hands-on experience managing infrastructure, understanding resource utilization, capacity planning
• Cost Consciousness: Experience analyzing and optimizing infrastructure costs at scale
• Distributed Systems: Strong fundamentals in distributed systems, concurrency, consistency models, and failure scenarios
• Accountability: Track record of taking full ownership—from design through deployment to ongoing operations and improvements

Preferred Qualifications:

• Experience with cloud platforms (GCP, AWS, or Azure) including cost management tools
• Kubernetes and container orchestration at scale
• Infrastructure as Code (Terraform, Pulumi, etc.)
• Streaming data systems (Kafka, Pub/Sub, Kinesis, Flink, etc.)
• SRE principles and reliability engineering practices
• Experience with FinOps or infrastructure cost optimization
• Performance profiling and optimization (CPU, memory, I/O)
• Technical leadership experience including mentorship of teams and driving multi-component initiatives
• Open source contributions or recognized technical writing

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