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
Qualifications
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.
