Ai system architect

Job Summary

We 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.

Job Requirements

Strong foundation in software engineering and system design Proven experience in building and scaling distributed systems Hands-on expertise in multiple programming languages (polyglot mindset) Solid experience with cloud-native architectures and microservices Practical experience building AI/ML systems in production at scale LLM integrations and orchestration LLM evaluation frameworks (evals) Multi-model strategies and guardrails Expertise in real-time data processing and streaming architectures Performance optimization System reliability & observability Security best practices Ability to balance architecture vision with hands-on execution

Job Responsibilities

Work hands-on with engineering teams, contribute to code, reviews, and technical problem-solving Architect and design scalable, resilient, and high-performance AI systems for production environments Design and implement agentic workflows and AI-first architectures Build and manage data-intensive, distributed systems with real-time processing capabilities Integrate and orchestrate multiple AI/ML models (including LLMs) with appropriate guardrails Establish strong engineering practices, including: Code quality & testing standards Feedback loops & observability Fitness functions for architecture governance Drive cloud-native architecture decisions (AWS/GCP/Azure) Ensure systems meet security, scalability, and performance benchmarks Lead technical discussions, mentor teams, and guide pragmatic technology decisions Collaborate with cross-functional stakeholders to translate business problems into robust technical solutions

Benefits

Innovative Engineering: Collaborative, fail-fast, flat hierarchy. Fosters learning, initiative, curiosity. Masterful Development: Emphasizes clean code, SOLID principles, TDD/BDD. Utilizes robust CI/CD and polyglot engineering. Continuous Growth: Structured mentorship, masterclasses, Geeknights, workshops, continuous skill enhancement, blog contributions. Agile & Client-Centric: Adopts Agile (Scrum, XP), promotes project ownership and deep client understanding for impactful solutions. Supportive Environment: Healthy work-life balance, flexible schedules, comprehensive benefits (generous leave), strong team-building.