Architecture & Design
o Define end‑to‑end reference architectures leveraging AWS services (e.g., VPC, ALB/NLB, EC2, ECS/EKS, Lambda, API Gateway, S3, DynamoDB/Aurora, OpenSearch, CloudFront, Route 53).
o Engineer for resiliency and availability: multi‑AZ patterns, active‑active/active‑passive, cross‑Region DR, RTO/RPO targets, automated failover, throttling, retries, DLQs, and circuit breakers.
o Drive security‑by‑design using IAM least privilege, KMS, Secrets Manager, VPC endpoints/PrivateLink, WAF/Shield, GuardDuty, Security Hub, and threat‑modeling practices.
• Hands‑on experience building Generative AI applications on AWS using LangGraph, including:
o Designing and orchestrating multi‑step agent workflows with LangGraph for tasks such as retrieval‑augmented generation (RAG), tool‑calling, workflow branching, and stateful interactions.
o Integrating LangGraph with Amazon Bedrock (model invocation, guardrails, embeddings, Knowledge Bases, Agents) and AWS services such as Lambda, API Gateway, Step Functions, DynamoDB, and S3.
o Implementing secure, scalable, and cost‑optimized GenAI patterns—evaluation, prompt management, latency optimization, caching strategies, and content‑safety controls.
o Building production‑ready GenAI microservices or platform components with observability (logs, metrics, traces), CI/CD, and automated testing.
Build & Platform Engineering
o Lead Infrastructure as Code (AWS CDK/Terraform/CloudFormation), Git‑based workflows, and automated pipelines (CodePipeline/GitHub Actions/Azure DevOps) across environments.
o Set observability standards (CloudWatch, X‑Ray, OpenTelemetry), SLO/error budgets, log/trace correlation, and automated runbooks.
• Performance, Reliability & Cost
o Execute load and chaos testing; capacity planning; autoscaling policies; data partitioning and caching.
o Optimize TCO using Savings Plans/Reserved Instances, Graviton adoption, right‑sizing, storage lifecycle policies, and cost allocation tags.
• Leadership & Stakeholder Management
o Act as technical lead for cross‑functional squads; decompose initiatives into deliverable architecture epics.
o Partner with Product, Security, and Operations to shape roadmaps and acceptance criteria; communicate decisions and trade‑offs clearly to senior stakeholders.
o Mentor engineers; uplift engineering standards and architectural rigor through reviews and guilds.
Basic Qualifications
• 8+ years designing and building production systems on AWS, including at least 3 years in an architect/tech‑lead role with hands‑on development.
• Proven delivery of highly available, highly resilient services at scale (multi‑AZ and cross‑Region patterns, DR strategy with defined RTO/RPO).
• Expert‑level development experience in one or more languages (TypeScript/Node.js, Python, or Java) and with microservices/serverless/container platforms (Lambda, ECS/Fargate, EKS).
• Deep knowledge of AWS networking (VPC, subnets, routing, NAT, TGW, PrivateLink), security (IAM/KMS/Secrets Manager), and data (DynamoDB, Aurora, S3, event streaming with SNS/SQS/Kinesis).
• Hands‑on experience delivering GenAI solutions on Amazon Bedrock (models, guardrails, RAG, Knowledge Bases) and integrating with enterprise data sources.
• Strong command of IaC, CI/CD, testing automation, and observability.
Preferred Qualifications
• Certifications:
o AWS Certified Solutions Architect – Professional (required)
o AWS Certified DevOps Engineer – Professional (preferred)
o AWS AI/ML or Generative AI specialty (preferred, if available)
• Experience with SageMaker (JumpStart, model hosting/tuning) and vector search (OpenSearch, pgvector).
• Familiarity with Zero‑Trust, security compliance (e.g., SOC2/PCI/ISO 27001), DLP, and data residency practices.
• Background with event‑driven and streaming architectures; schema governance; idempotency and eventual consistency patterns.
• Prior ownership of migration/modernization programs (monolith to microservices, on‑prem to AWS, or lift‑and‑evolve).
Soft Skills (Critical)
• Executive‑quality communication: clear, concise narratives and visuals for both technical and non‑technical audiences.
• Tech lead & mentoring: setting guardrails, conducting design/code reviews, enabling teams to move independently.
• Stakeholder management: roadmap alignment, expectation setting, risk/issue management, and conflict resolution.
• Product mindset: outcome‑driven, data‑informed decisions; bias for automation and iterative delivery.