Role Overview: The AI Agentic Architect defines enterprise vision, target architectures, and operational foundations for autonomous AI agent ecosystems and LLM orchestration platforms. This leader steers multi-agent frameworks, cognitive workflows, retrieval-augmented generation (RAG), and enterprise tool integrations, ensuring that autonomous agent solutions are robust, compliant, scalable, and strategically aligned with organizational objectives.

Key Responsibilities & Architectural Oversight

- Formulate holistic architectural blueprints for multi-agent autonomous workflows, energetic task planners, agent memory topologies, and tool-use protocols.
- Architect high-throughput, low-latency LLM orchestration pipelines leveraging LangChain, LangGraph, AutoGen, CrewAI, Semantic Kernel, and custom agents.
- Design advanced RAG pipelines incorporating semantic vector stores (Pinecone, Weaviate, Milvus, Qdrant), hybrid search, re-ranking, and chunking strategies.
- Establish enterprise AI safety frameworks, guardrails (NeMo, Llama Guard), prompt injection defense, hallucination mitigations, and PII anonymization.
- Define agent evaluation protocols, ground truth benchmarking, automated evals, and performance observability across token usage, cost, and latency.




- Direct enterprise integration patterns connecting autonomous agents with ERP, CRM, internal REST APIs, SQL databases, and enterprise data warehouses.
- Guide infrastructure sizing, containerized orchestration on Kubernetes, GPU compute optimization, and cloud provider deployments across Azure, AWS, and GCP.

Governance & Strategic Direction

- Formulate organizational standards for model selection, SLMs vs. LLMs, fine-tuning methodologies, context window management, and fallback mechanisms.
- Establish comprehensive architectural governance, reviewing agent capabilities, decision trees, permissions, and human-in-the-loop escalation paths.
- Conduct threat modeling and risk assessments for agent autonomous execution, mitigating unintended side effects and ensuring auditability.

Stakeholder Alignment & Innovation

- Advise executive leadership and business stakeholders on generative AI opportunities, technical feasibility, ROI analysis, and risk tradeoffs.
- Partner with security, legal, and compliance officers to guarantee compliance with global AI regulations, data privacy mandates, and corporate policies.

📌 Systems Architect (Hyderabad)
🏢 Virtusa
📍 Hyderabad