About the company
This position is listed on behalf of a partner company, who manages all applications and next steps. The partner is looking for a Chief Technical Architect, Engineering (IC Role) based in India.
Responsibilities
- Define and communicate a three-to-five-year technology strategy and architecture roadmap with the CTO and product leadership
- Own the architecture of large-scale SaaS platforms, including multi-tenant and multi-region services
- Establish architectural principles and technical guardrails for reliability, performance, security, scalability, and cost
- Lead the architecture of generative AI and Agentic AI platforms: LLM orchestration, RAG, vector search, evaluation pipelines, observability, model governance
- Guide evolution of data platforms: streaming architectures, lakehouse solutions, analytics, SQL/NoSQL systems
- Establish architecture review forums, design standards, and technical governance processes
- Identify and resolve systemic technical risks and performance bottlenecks
- Lead build-versus-buy assessments, technology evaluations, and vendor decisions
- Evaluate technology investments using TCO, unit economics, and scalability
- Translate ambiguous business ideas into clear technical designs
- Mentor principal engineers and emerging architects
- Partner with product executives, engineering leaders, QA, DevOps, and SRE teams
- Communicate complex technical concepts to executive stakeholders
- Establish measurable technical outcomes and improve platform quality
Requirements
- Bachelor's or master's degree in Computer Science, IT, Engineering, or related discipline
- 15+ years of software engineering experience, including at least 5 years in an architect or principal-level role
- Experience in a product-led organization, ideally SaaS, with architecture responsibility across multiple teams
- Ability to influence large engineering organizations (50+ engineers)
- Deep expertise in cloud-native architecture, distributed computing, microservices, event-driven systems, and modern data architectures
- Hands-on experience with production-grade generative AI or Agentic AI systems: LLM orchestration, RAG pipelines, vector databases, evaluation frameworks, AI observability
- Strong software engineering fundamentals: data structures, algorithms, OOP
- Proficiency in Java, Python, Scala, Go, or Node.js
- Ability to establish enterprise-level governance for software quality, performance, resilience, security, and data privacy
- Track record of measurable technical impact
- Experience with platform consolidation, cloud migration, or monolith-to-platform transformation is a strong advantage
- Strong influencing, communication, and stakeholder management skills
- Experience in ERP, supply chain, or manufacturing software is a plus