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Lead - Agentic AI

Quadrasystems.net India Private Limited

AWS SBU - (2026)

Role Overview

The Lead - Agentic AI serves as Quadrasystems senior technical authority for Agentic AI architecture within the AWS Strategic Business Unit (SBU). You will own the design and delivery of enterprise-grade multi-agent systems built on Amazon Bedrock and AWS AgentCore, lead a team of Agentic AI engineers, and drive the practice s growth through client engagements, thought leadership, and reusable accelerator development. This role demands both deep expertise in agentic architecture and the ability to translate complex AI capabilities into measurable business value.

Key Responsibilities

Technical Leadership

- Define the Agentic AI architecture standard for Quadrasystems AWS practice, including agent design patterns, tool integration, memory management, governance, and observability.
- Lead the design and delivery of multi-agent systems on Amazon Bedrock Agents and AWS AgentCore, covering orchestrator-subagent patterns, hierarchical agents, and agent-as-tool architectures.
- Architect Retrieval-Augmented Generation (RAG) pipelines at enterprise scale, including embedding strategy, vector store selection (OpenSearch Serverless, Aurora pgvector), hybrid search, and re-ranking for production accuracy.
- Establish prompt governance frameworks, such as system prompt standards, chain-of-thought patterns, guardrails configuration, and hallucination mitigation strategies.
- Evaluate foundation models (Claude, Nova, Titan, Llama, Mistral) across accuracy, cost, latency, and safety dimensions for specific client use cases.

Delivery & Client Engagement

- Lead Agentic AI presales activities, including use case discovery, feasibility assessment,



platform selection (AgentCore vs. Amazon Q), and business case development.
- Own technical delivery for Agentic AI engagements from proof-of-concept through production, including evaluation frameworks, deployment architecture, and post-deployment monitoring.
- Present architecture designs and delivery progress to CXO-level client stakeholders.
- Build Quadrasystems Agentic AI accelerator library, including reusable agent templates, tool connectors, evaluation harnesses, and deployment patterns.

Team & Practice Development

- Mentor and guide a team of Agentic AI engineers through architecture reviews, prompt reviews, and skill development.
- Collaborate with the Cloud Center of Excellence (CCoE) team on governance, IAM, and observability standards for Agentic AI workloads.
- Contribute to Quadrasystems market positioning by writing technical content, presenting at AWS events, and leading internal capability workshops.

Technical Skills Required

AWS Agentic AI Services (Expert Level)

- Amazon Bedrock: Foundation models, Bedrock Agents, Knowledge Bases, Guardrails, Evaluations, Model Customisation
- AWS AgentCore: Runtime, Gateway (MCP), Memory, Identity, Policy, Observability, Code Interpreter
- Amazon Bedrock Inline Agents and Multi-Agent Collaboration
- AWS Lambda, Amazon API Gateway, AWS Step Functions, Amazon EventBridge
- Amazon OpenSearch Serverless, Aurora pgvector, DynamoDB, ElastiCache





Underlying AI/ML Technologies (Expert Level)

- LLM architecture: Transformer models, attention mechanisms, context windows, tokenisation
- Agentic frameworks: LangGraph, CrewAI, AutoGen, Strands Agents - architecture patterns and trade-offs
- RAG: Advanced patterns (HyDE, FLARE, contextual compression, multi-hop retrieval)
- MCP (Model Context Protocol): Server design, tool schemas, authentication patterns
- Agent evaluation: LLM-as-judge, human evaluation, automatic metrics (RAGAS, TruLens)
- Fine-tuning: LoRA, QLoRA, SFT - application versus RAG-first approach
- Multi-agent protocols: A2A, ACP, orchestration patterns (swarm, hierarchical, peer-to-peer)
- Python: Advanced (asyncio, Pydantic, FastAPI, boto3)

Valuable to Have

- AWS Certified AI Practitioner (Advanced) or AWS Certified Machine Learning - Specialty
- Published thought leadership (blog posts, conference talks, or open-source contributions in Agentic AI)
- Exposure to Amazon Q Business and Amazon Q Developer architectures

Qualifications

- Bachelor s or Master s degree in Computer Science, Artificial Intelligence, or a related field
- 4+ years of technical experience, with at least 2 years working directly with LLMs, Generative AI, or Agentic AI systems in production or client-facing roles
- Proven track record of leading technical teams or mentoring junior engineers in AI/ML or software engineering

Confidential Quadrasystems.net

Quadrasystems.net India Private Limited

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 Lead - Agentic AI (Bengaluru)
🏢 Quadrasystems.Net
📍 Bengaluru