GEN AI Architect / Sr Architect (AWS - Presales / Sales Expert)

Looking for a highly skilled GenAI and Agentic AI Architect with deep hands-on expertise across AWS AI/ML services, multi-agent systems, LLM orchestration, and cloud-native engineering. This role centers on architecting and delivering scalable, secure, production-grade GenAI solutions using AWS AgentCore, AWS Bedrock, AWS Strands SDK, vector databases, and Python-based agentic AI solutions. You will define reference architectures, code solutions, lead complex implementations, and drive adoption of advanced GenAI and agentic patterns across enterprise systems.

Key Responsibilities

• Experience in pre-sales, solutioning, and deal shaping for large digital transformation programs.

GenAI & Agentic AI Architecture

• Architect end-to-end GenAI-first and Agentic AI solutions on AWS using:

• Amazon Bedrock
• Amazon AgentCore
• Strands SDK Multi-Agents
• AWS Agents for Bedrock
• Knowledge Bases for Bedrock
• Guardrails for Bedrock

• Amazon SageMaker for model lifecycle & finetuning

• Design multi-agent systems supporting planning, reasoning, tool invocation, memory stores, and multi-step workflows.

• Develop high-performance RAG architectures using:

• Amazon OpenSearch Serverless
• Kendra
• Aurora + pgvector

• Redis Enterprise

• Implement secure prompt flows, tool integrations, embeddings pipelines, and evaluation frameworks optimized for AWS.

Application & Platform Engineering

• Build Python-based microservices (FastAPI/Django) integrated with AWS AI stack.

• Design scalable architectures using AWS-native components:

• Lambda, Step Functions, EventBridge, SQS, DynamoDB, API Gateway, ECS/EKS

• Implement enterprise-class LLMOps using:

• Amazon SageMaker Pipelines
• AWS CodePipeline / CodeBuild

• CloudWatch / X-Ray observability

• Establish standards for:

• Agent governance & safety
• Secure model invocation
• Guardrails & content filters
• Latency & cost optimization patterns

Security, Reliability & Optimization

• Ensure compliance with enterprise security standards using:

• IAM, KMS, VPC endpoints, PrivateLink, CloudTrail

• Optimize AI workloads for cost, performance, and scalability, including model caching, selective batching, and autoscaling strategies.
• Conduct architecture reviews, threat modeling, and performance benchmarking.

Innovation & Framework Evangelism

• Assess new AWS AI services, foundation models, agent frameworks, and vector DBs.

• Create internal accelerators, reusable patterns, and AWS-focused reference architectures for:

• Multi-agent orchestration
• RAG 2.0 / context enrichment
• Federated retrieval

• Enterprise tool integration

• Lead PoCs, prototypes, and technical spikes to validate emerging AWS GenAI capabilities.

Technical Mentorship & Enablement

• Mentor engineering teams on AWS GenAI patterns, LLMOps, cloud-native development, and distributed AI architectures.
• Provide technical direction, best practices, and deep architectural guidance across delivery teams.
• Create internal documentation, architecture blueprints, and engineering playbooks.

Required Skills & Qualifications

• AWS Certified Associate/Professional Solutions Architect.

Preferred Qualifications

• Expert-level experience with AWS Bedrock, AWS AgentCore, Strands SDK, AWS Agents, SageMaker, OpenSearch, Lambda, Step Functions, ECS/EKS, and DynamoDB.
• Strong Python development background (FastAPI, Django).

• Hands-on coding ability with:

• Enterprise RAG
• Agent orchestration frameworks (Strands, LangGraph, CrewAI, Bedrock Agents, etc.)
• Embedding models and vector DB design
• Exposure to data engineering, analytics, and AI-driven platforms.