Principal AI Solution Architect (Agentic Systems)

Minutes to Seconds; Arishinakunte; On-site; INR 2,000,000 - 3,000,000; Full time

Job summary

Minutes to Seconds is looking for a Principal AI Solution Architect to lead technical visions for their enterprise AI projects in Arishinakunte, Karnataka. The role demands 13+ years of experience, including 3+ years in Generative AI Architecture. You will design and architect systems where advanced AI integrates with existing enterprise infrastructures. Key responsibilities include technical leadership, cost optimization, and mentoring engineering teams. A Bachelor’s or Master’s in CS or related fields is required, along with significant experience in AI tools and frameworks.

Qualifications

• 13+ years of experience in AI, with over 3 years in Generative AI Architecture.
• Proven track record of leading enterprise-grade AI projects.

Responsibilities

• Lead the technical vision for complex enterprise AI engagements.
• Architect the Sovereign AI infrastructure and multi-agent orchestration layers.
• Design integration patterns to connect LLMs with existing systems.
• Build safety frameworks to ensure compliance in regulated sectors.
• Optimize costs and performance through strategic architectural decisions.
• Mentor senior engineers and lead collaboration with stakeholders.

Skills

Expert-level mastery of LangGraph

Semantic Kernel

Autogen

Pydantic AI

LangChain

LlamaIndex

Kubernetes

Docker

Vector DBs (Pinecone, Milvus)

Graph DBs (Neo4j)

Education

Bachelor's or Master's in CS, AI, or related field

Certifications in AWS/Azure/GCP AI Architecture

Job description

Experience: 13+ Years (3+ in Generative AI Architecture)

The Vision

As a Principal AI Solution Architect, you will lead the technical vision for our most complex enterprise AI engagements. You won't just choose a model; you will architect the Sovereign AI infrastructure, multi-agent orchestration layers, and the governance frameworks that allow companies to move from experimental assistants to autonomous Agentic workforces.

Strategic Responsibilities

• Architecture Blueprinting: Define the target-state architecture for multi-agent systems, including decision‑making on component selection (Orchestrator vs. Routers), cloud topology (Public, Hybrid, or Air-gapped), and deployment models.
• Agentic Design Patterns: Implement advanced patterns like Interleaved Decomposition (Plan-Act-Reflect) and Multi-Agent Collaboration to solve non-linear, high-stakes business processes.
• Enterprise Integration (The "Action" Layer): Design standard integration patterns to bridge LLMs with legacy ERPs, SAP, and custom data lakes.
• Governance & Trust: Build the Safety Scaffolding including guardrails, PII masking, and automated LLM-as-a-Judge evaluation pipelines to ensure compliance in regulated sectors (Pharma, Finance, 5G).
• Cost & Performance Optimization: Architect for ‘Smarter, not Larger’ Implement strategies for context compression, model routing (small-model vs. large-model logic), and semantic caching to maximize ROI.
• Leadership & Mentorship: Lead discovery sessions with C-suite stakeholders, manage technical risk across globally distributed engineering teams, and mentor Senior AI Engineers on best practices.

Core Technical Stack & Expertise

• Orchestration: Expert-level mastery of LangGraph, Semantic Kernel, or Autogen.
• Frameworks: Deep experience with Pydantic AI, LangChain, and LlamaIndex for stateful, complex RAG and Agentic workflows.
• Infrastructure: Proficiency in Kubernetes, Docker, and AI gateways and experience with Sovereign AI tools.
• Data Strategy: Advanced knowledge of Vector DBs (Pinecone, Milvus), Graph DBs (Neo4j), and hybrid search strategies.

Requirements

• Proven Track Record: You have successfully led at least two enterprise-grade AI projects from initial architecture through to global production deployment.
• Consultative Mindset: Ability to translate vague business requirements into a robust technical roadmap and a "Build vs. Buy" analysis.

Education

• Bachelor's or Master's in CS, AI, or a related field. Professional
• Certifications in AWS/Azure/GCP AI Architecture are highly preferred.