Principal Architect - AI & Full Stack

Sigma Infosolutions Ltd.; Bengaluru; On-site; INR 3,500,000 - 5,500,000; Full time

Job summary

Sigma Infosolutions Ltd. seeks a Principal Architect - AI & Full Stack to lead hands-on architectural work across AI/GenAI and full-stack platforms in Bengaluru, with exposure to multiple locations.

The role combines building reusable AI services with defining scalable, API-first architectures and governance for secure, production-ready systems. You will drive POCs, scale AI capabilities, and ensure alignment with client needs while mentoring teams in modern engineering accelerators and

Qualifications

• Hands-on, architectural leadership across UI, workflows, business rules and integrations.
• Define API-first, event-driven, microservices-based architectures.
• Govern architecture quality for robust, scalable, secure, maintainable systems.

Responsibilities

• Architect and build AI/GenAI solutions including LLMs, embeddings, vector databases, RAG and agent orchestration.
• Lead AI POCs from discovery to production readiness.
• Develop reusable AI services and accelerators for multiple products/clients/tenants.
• Define and govern semantic/knowledge architecture to support AI-enabled apps.

Skills

Solution Architect

Client Facing

React JS

AI/GenAI

APIs

Microservices

Event-driven

Architecture Governance

AI Observability

Job description

#### Principal Architect - AI & Full Stack###### Job Code: SIL-48011Bengaluru, Karnataka, India+ 2 more1 positionRequired Experience8 - 12 YearsSkillsSolution Architect,Client Facing,React JS+ 15 more**Experience:** 8-12 years**Location:** Bangalore / Ahmedabad / JodhpurWe are looking for a **strong** **hands-on, forward-thinking Technical pioneer** who can split their time between two critical mandates:- Establish reusable, **configuration-driven** architecture for UI, workflows, business rules, validations, integrations, permissions, feature flags, and tenant-specific requirements.- Define **API-first, event-driven, microservices/modular** architectures and integration patterns based on business and scalability requirements.- Govern architecture quality and technical decisions, ensuring systems remain **robust, scalable, secure, maintainable, and production-ready** while supporting continuous onboarding of new tenant requirements.* Architect and build **AI/GenAI solutions** including LLMs, model routing, embeddings, vector databases, hybrid search, RAG, tool/function calling, MCP, agent orchestration, guardrails, and AI observability.* **Lead AI POCs** from business use-case discovery and architecture through prototype, evaluation, integration, and production-readiness assessment.* Build reusable AI services and accelerators that can be consumed across multiple products, clients, and tenants rather than developing isolated project-specific solutions.* Define configuration-driven AI capabilities including tenant-specific models, prompts, tools, knowledge sources, policies, workflows, and AI features.* Define and govern the architecture of the **semantic layer, ontology, knowledge representation, and related knowledge/semantic architecture** required to support AI-enabled applications and intelligent workflows.* Drive **Vibe Coding-based application development** and establish reusable **Agentic AI-assisted development** workflows, templates, prompts, skills, coding agents, and engineering accelerators.* Identify opportunities to use **AI agents across the SDLC**, including requirement analysis, architecture, coding, code review, testing, debugging, documentation, migration, and DevOps automation.* Identify opportunities to apply **AI to improve engineering productivity**, automate business processes, reduce operational overhead, and create new client-facing capabilities.* Collaborate with leadership to define the **AI technology roadmap**, reusable accelerators, reference architectures, and AI Center of Excellence capabilities.* **Track emerging AI technologies** and evaluate their applicability across client engagements and industry-specific use cases.- Bring practical experience in **implementing, deploying, and operationalizing AI/GenAI solutions in production environments**.