AI Systems Architect

AI Systems Architect

Job Summary

We are actively looking for a 10+ years of hands-on 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

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

Job Responsibilities

1. Work hands-on with engineering teams, contribute to code, reviews, and technical problem-solving
2. Architect and design scalable, resilient, and high-performance AI systems for production environments
3. Design and implement agentic workflows and AI-first architectures
4. Build and manage data-intensive, distributed systems with real-time processing capabilities
5. Integrate and orchestrate multiple AI/ML models (including LLMs) with appropriate guardrails
6. Establish strong engineering practices, including:
7. . Code quality & testing standards
8. . Feedback loops & observability
9. . Fitness functions for architecture governance
10. Drive cloud-native architecture decisions (AWS/GCP/Azure)
11. Ensure systems meet security, scalability, and performance benchmarks
12. Lead technical discussions, mentor teams, and guide pragmatic technology decisions
13. 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.