AI System Architect

Job Summary\n\nWe are actively looking for a 10-12 years of hands-on experience Architect with a strong engineering foundation, polyglot expertise, and deep experience in building AI systems at scale. This role goes beyond high-level system design; you will be expected to think like an engineer, contribute to code, and architect scalable, production-grade platforms powered by modern AI capabilities. You will play a key role in designing and delivering next-generation AI-driven solutions for global clients, including agentic workflows, intelligent automation systems, and data-intensive platforms.\n\nJob Requirements\n\n- Strong foundation in software engineering and system design\n- Proven experience in building and scaling distributed systems\n- Hands-on expertise in multiple programming languages (polyglot mindset)\n- Solid experience with cloud-native architectures and microservices\n- Practical experience building AI/ML systems in production at scale\n- LLM integrations and orchestration\n- LLM evaluation frameworks (evals)\n- Multi-model strategies and guardrails\n- Expertise in real-time data processing and streaming architectures\n- Performance optimization\n- System reliability & observability\n- Security best practices\n- Ability to balance architecture vision with hands-on execution\n\nJob Responsibilities\n\n- Work hands-on with engineering teams, contribute to code, reviews, and technical problem-solving\n- Architect and design scalable, resilient, and high-performance AI systems for production environments\n- Design and implement agentic workflows and AI-first architectures\n- Build and manage data-intensive, distributed systems with real-time processing capabilities\n- Integrate and orchestrate multiple AI/ML models (including LLMs) with appropriate guardrails\n- Establish strong engineering practices, including:\n- Code quality & testing standards\n- Feedback loops & observability\n- Fitness functions for architecture governance\n- Drive cloud-native architecture decisions (AWS/GCP/Azure)\n- Ensure systems meet security, scalability, and performance benchmarks\n- Lead technical discussions, mentor teams, and guide pragmatic technology decisions\n- Collaborate with cross-functional stakeholders to translate business problems into robust technical solutions\n\nBenefits\n\n- Innovative Engineering: Collaborative, fail-fast, flat hierarchy.