We are looking for an experienced Principal Engineer – Backend & AI to provide technical leadership across backend engineering, distributed systems, cloud-native platforms, and AI-powered solutions.
The ideal candidate will be a hands-on technology leader with deep expertise in Java/Spring Boot, microservices, scalable architectures, APIs, cloud platforms, and modern AI/GenAI technologies. You will work closely with engineering, product, architecture, and business teams to define technology strategy, solve complex engineering problems, and build highly scalable and intelligent products.
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Define and drive the architecture and technology strategy for highly scalable backend platforms.
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Design robust, secure, resilient, and high-performance distributed systems.
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Provide technical leadership across multiple engineering teams and complex initiatives.
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Establish architecture standards, design principles, coding standards, and engineering best practices.
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Drive technology modernization, platform transformation, and cloud adoption.
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Review and influence critical architectural and technical decisions across the organization.
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Act as a technical mentor and thought leader for Senior Engineers, Tech Leads, and Engineering Managers.
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Design and develop scalable backend services using Java and Spring Boot.
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Build and evolve microservices, RESTful APIs, event-driven systems, and distributed applications.
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Drive performance optimization, scalability, reliability, and availability of backend platforms.
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Work with databases, caching, messaging, and distributed data technologies.
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Design solutions for high-throughput and low-latency workloads.
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Lead technical initiatives involving refactoring, modernization, and migration of legacy platforms.
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Identify opportunities to integrate AI and Generative AI capabilities into products and engineering platforms.
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Design and implement AI-powered backend services and intelligent applications.
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Work with LLMs, RAG, embeddings, vector databases, prompt engineering, AI agents, and AI orchestration frameworks.
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Integrate commercial and/or open-source AI models through APIs and enterprise AI platforms.
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Design scalable architectures for AI inference, model integration, evaluation, monitoring, and governance.
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Partner with Data Science and ML teams to productionize AI/ML solutions.
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Evaluate emerging AI technologies and translate them into practical business and engineering solutions.
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Establish best practices for responsible, secure, and cost-effective use of GenAI
