Senior Architect - R01558324

Team: Infrastructure Engineering : Infrastructure Engineering

Location: Bangalore, Karnataka, India

Commitment: Employee

Workplace Type: hybrid

Primary Skills

• AWS, AWS Elastic Beanstalk, AWS SageMaker, AWS CodeBuild, AWS Cloud FinOps, AWS Lambda, AWS DevOps, AWS Development, AWS CodeDeploy, AWS Serverless, AWS CodePipeline, AWS Cognito, AWS Managed Services, AWS EC2, AWS Infrastructure (Provisioning & Automation), AWS ELB, Solution Architecture - AWS, AWS Database, AI/ML, AWS QuickSight, AWS Step Function, AWS Security, AI in Design Process

Specialization

• AWS Architecture: Software Development Manager

Job requirements

• To succeed, this Role’s Responsibilities Would Involve: Architecture & Solutioning • Design AI-enabled architectures for highly available, scalable, efficient, secure, and optimized cloud infrastructure services and applications on AWS, using LLMs, Agentic AI, and services such as Amazon Bedrock and SageMaker. • Integrate AWS services (including cross-account) using AWS SDK for governance, security automation, provisioning frameworks, and cloud workflows. • Design event-driven architectures using API Gateway, Lambda, Step Functions, SQS/SNS, DynamoDB streams, CodeBuild etc. • Define and implement cloud adoption, modernization, and migration strategies. Frameworks & Reusable Platforms • Build reusable frameworks integrating AWS services to accelerate delivery of cloud-native and GenAI-based solutions. • Develop accelerators for serverless apps, CI/CD, AI inference pipelines, and cloud provisioning. DevOps, Infra Automation & Governance • Implement IaC using CloudFormation (expert-level), CDK, or Terraform (optional). • Build CI/CD automation using CodePipeline, CodeBuild, CodeDeploy. • Enable cloud security, observability, monitoring, logging, and compliance best practices. • Contribute to multi-account governance, Landing Zone / Control Tower design, and cross-account automation. AI/LLM Integration & Enablement • Architect and integrate GenAI and LLM-based features into enterprise applications. • Build inference pipelines, embeddings workflows, prompt-management layers, and RAG-based solutions. • Evaluate new AI offerings across AWS (Bedrock models, finetuning, Agents for Bedrock, Guardrails). • Provide guidance on scalable AI infrastructure, model selection, tuning, vector indexing, and latency optimization. Leadership & Collaboration • Guide and mentor engineering teams, remove technical blockers, and ensure delivery quality. • Support WBS creation, estimation, and SOW preparation for cloud and AI engagements. • Evaluate new AWS services and drive PoCs/PoVs with strong business justification. • Participate in architectural governance, design reviews, and solution accelerators. Mandatory Skills • 12+ years of overall experience; strong focus on application and infrastructure architecture (minimum 10 years in application dev/architecture in AWS services) • Extensive hands-on experience with AWS services: serverless and event-driven architecture (API Gateway, Lambda, DynamoDB, SQS, SNS, Step Functions, CodeBuild etc.) • Experience integrating AI/LLM capabilities using AWS Bedrock, SageMaker, OpenSearch, or similar stack. • Good experience with compute, network, storage, security, deployment, and automation in AWS • Expertise at the SDK level for AWS services (i.e., deep familiarity with how services are programmatically consumed) • Application development background (preferably Node.js or Python) • Focus on cost, capacity sizing, optimisation of AWS services (balancing performance, scale and investment) • Strong experience writing infrastructure-as-code (preferably AWS CloudFormation) • Experience with AWS native DevOps/CI/CD components (e.g., CodeBuild, CodePipeline, CodeDeploy) • Experience with version control systems (Git) • Solid understanding of networking, security, and architectural best-practices in cloud environments • Excellent communication skills (written and presentation) and ability to articulate architectural decisions clearly • Strong organisational/time-management discipline and ability to work across multiple workstreams Good To Have Skills • Experience with prompt engineering, embeddings, vector stores (OpenSearch, DynamoDB + vector indexing, Redis). • Experience with AWS RDS, DynamoDB advanced patterns (global tables, streams, TTLs, on-demand backup/restore) • Familiarity with service catalog, governance tooling, cross‐account provisioning, and framework development for enterprise cloud governance