Devlyn AI · AWS · Real Estate
AWS engineering for Real Estate. Shipped at 4× pace.
Deploy a senior AWS pod that understands Real Estate compliance natively. One retainer. Embedded in your team in 24 hours.
The intersection
Operating AWS in Real Estate is not just a syntax problem — it is an architectural and compliance challenge.
AWS pods ship cloud-native infrastructure spanning serverless architectures with Lambda and API Gateway, container orchestration with ECS/Fargate for predictable workloads and EKS for Kubernetes-native deployments, data-layer design with DynamoDB for key-value and document access patterns, RDS and Aurora for relational workloads with read replicas, S3 for object storage with lifecycle policies, event-driven architectures using EventBridge and SQS for decoupled service communication, and Step Functions for workflow orchestration. Devlyn engineers ship AWS with CDK (TypeScript or Python) or Terraform for infrastructure-as-code with modular construct patterns, OpenTelemetry for distributed tracing across serverless and container services, and cost-aware architecture choices including reserved-capacity planning, spot-instance strategies, and right-sizing recommendations — with production-grade IAM least-privilege policies and GuardDuty threat detection.
AI-augmented AWS workflows lean on Cursor and Claude Code for CDK construct scaffolding with proper resource configuration, Terraform module generation with variable and output definitions, Lambda handler patterns with proper error handling and cold-start optimisation, EventBridge rule and target configuration, and IAM policy generation with least-privilege scoping — all under senior validation that owns architecture decisions, cost-budget review and optimisation (reserved instances, savings plans, spot strategies), IAM security posture with service-control policies and permission boundaries, and AWS-specific pitfalls like Lambda cold-start mitigation, DynamoDB partition-key design for even distribution, and cross-region replication configuration. Compression shows up strongest in IaC module scaffolding, Lambda handler boilerplate, and IAM policy generation.
Where this pod lands today
Browse how this exact AWS and Real Estate combination maps to different talent markets.
AWS · Real Estate · New York
AWS for Real Estate in New York
The most common 2026 real-estate engineering trap is shipping a feature that depends on an MLS data-access agreement or mortgage-partner integration that has not been contractually finalised, creating a market-by-market deployment blocker. AWS pods compress the work — aws pods ship cloud-native infrastructure spanning serverless architectures with lambda and api gateway, container orchestration with ecs/fargate for predictable workloads and eks for kubernetes-native deployments, data-layer design with dynamodb for key-value and document access patterns, rds and aurora for relational workloads with read replicas, s3 for object storage with lifecycle policies, event-driven architectures using eventbridge and sqs for decoupled service communication, and step functions for workflow orchestration. On the Eastern (ET) calendar, fte-only paths to scale engineering in nyc routinely run 2–3 quarters behind the roadmap.
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AWS · Real Estate · San Francisco
AWS for Real Estate in San Francisco
The most common 2026 real-estate engineering trap is shipping a feature that depends on an MLS data-access agreement or mortgage-partner integration that has not been contractually finalised, creating a market-by-market deployment blocker. AWS pods compress the work — aws pods ship cloud-native infrastructure spanning serverless architectures with lambda and api gateway, container orchestration with ecs/fargate for predictable workloads and eks for kubernetes-native deployments, data-layer design with dynamodb for key-value and document access patterns, rds and aurora for relational workloads with read replicas, s3 for object storage with lifecycle policies, event-driven architectures using eventbridge and sqs for decoupled service communication, and step functions for workflow orchestration. On the Pacific (PT) calendar, fte hiring in sf has slowed structurally since 2024 layoffs but compensation expectations have not.
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AWS · Real Estate · Los Angeles
AWS for Real Estate in Los Angeles
The most common 2026 real-estate engineering trap is shipping a feature that depends on an MLS data-access agreement or mortgage-partner integration that has not been contractually finalised, creating a market-by-market deployment blocker. AWS pods compress the work — aws pods ship cloud-native infrastructure spanning serverless architectures with lambda and api gateway, container orchestration with ecs/fargate for predictable workloads and eks for kubernetes-native deployments, data-layer design with dynamodb for key-value and document access patterns, rds and aurora for relational workloads with read replicas, s3 for object storage with lifecycle policies, event-driven architectures using eventbridge and sqs for decoupled service communication, and step functions for workflow orchestration. On the Pacific (PT) calendar, la's hiring funnel competes with sf for senior talent at lower compensation envelopes.
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AWS · Real Estate · Boston
AWS for Real Estate in Boston
The most common 2026 real-estate engineering trap is shipping a feature that depends on an MLS data-access agreement or mortgage-partner integration that has not been contractually finalised, creating a market-by-market deployment blocker. AWS pods compress the work — aws pods ship cloud-native infrastructure spanning serverless architectures with lambda and api gateway, container orchestration with ecs/fargate for predictable workloads and eks for kubernetes-native deployments, data-layer design with dynamodb for key-value and document access patterns, rds and aurora for relational workloads with read replicas, s3 for object storage with lifecycle policies, event-driven architectures using eventbridge and sqs for decoupled service communication, and step functions for workflow orchestration. On the Eastern (ET) calendar, boston fte pipelines run 4–6 months for senior backend roles.
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AWS · Real Estate · Chicago
AWS for Real Estate in Chicago
The most common 2026 real-estate engineering trap is shipping a feature that depends on an MLS data-access agreement or mortgage-partner integration that has not been contractually finalised, creating a market-by-market deployment blocker. AWS pods compress the work — aws pods ship cloud-native infrastructure spanning serverless architectures with lambda and api gateway, container orchestration with ecs/fargate for predictable workloads and eks for kubernetes-native deployments, data-layer design with dynamodb for key-value and document access patterns, rds and aurora for relational workloads with read replicas, s3 for object storage with lifecycle policies, event-driven architectures using eventbridge and sqs for decoupled service communication, and step functions for workflow orchestration. On the Central (CT) calendar, chicago fte hiring runs 3–5 months for senior roles with reasonable base salaries vs coast hubs.
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AWS · Real Estate · Seattle
AWS for Real Estate in Seattle
The most common 2026 real-estate engineering trap is shipping a feature that depends on an MLS data-access agreement or mortgage-partner integration that has not been contractually finalised, creating a market-by-market deployment blocker. AWS pods compress the work — aws pods ship cloud-native infrastructure spanning serverless architectures with lambda and api gateway, container orchestration with ecs/fargate for predictable workloads and eks for kubernetes-native deployments, data-layer design with dynamodb for key-value and document access patterns, rds and aurora for relational workloads with read replicas, s3 for object storage with lifecycle policies, event-driven architectures using eventbridge and sqs for decoupled service communication, and step functions for workflow orchestration. On the Pacific (PT) calendar, seattle fte pipelines compete with faang-tier salaries that startup budgets cannot match.
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Common questions
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Why hire a AWS pod specifically for Real Estate?
Because AWS in Real Estate requires specific architectural patterns. undefined Devlyn's pods bring both the deep AWS ecosystem knowledge and the Real Estate regulatory context on day one.
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What does the AWS pod own end-to-end?
Architecture, security review, and the AWS-specific patterns that production-grade work requires. AWS pods ship cloud-native infrastructure spanning serverless architectures with Lambda and API Gateway, container orchestration with ECS/Fargate for predictable workloads and EKS for Kubernetes-native deployments, data-layer design with DynamoDB for key-value and document access patterns, RDS and Aurora for relational workloads with read replicas, S3 for object storage with lifecycle policies, event-driven architectures using EventBridge and SQS for decoupled service communication, and Step Functions for workflow orchestration. Devlyn engineers ship AWS with CDK (TypeScript or Python) or Terraform for infrastructure-as-code with modular construct patterns, OpenTelemetry for distributed tracing across serverless and container services, and cost-aware architecture choices including reserved-capacity planning, spot-instance strategies, and right-sizing recommendations — with production-grade IAM least-privilege policies and GuardDuty threat detection.
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How do AI-augmented workflows help in Real Estate?
AI-augmented AWS workflows lean on Cursor and Claude Code for CDK construct scaffolding with proper resource configuration, Terraform module generation with variable and output definitions, Lambda handler patterns with proper error handling and cold-start optimisation, EventBridge rule and target configuration, and IAM policy generation with least-privilege scoping — all under senior validation that owns architecture decisions, cost-budget review and optimisation (reserved instances, savings plans, spot strategies), IAM security posture with service-control policies and permission boundaries, and AWS-specific pitfalls like Lambda cold-start mitigation, DynamoDB partition-key design for even distribution, and cross-region replication configuration. Compression shows up strongest in IaC module scaffolding, Lambda handler boilerplate, and IAM policy generation. In Real Estate, this compression is particularly valuable for accelerating The most common 2026 real-estate engineering trap is shipping a feature that depends on an MLS data-access agreement or mortgage-partner integration that has not been contractually finalised, creating a market-by-market deployment blocker. Second is fair-housing algorithmic-bias exposure in listing recommendation or tenant-screening algorithms that can trigger HUD enforcement action. Devlyn pods design around partner-contract reality and build fair-housing bias testing into the CI/CD pipeline. without compromising the compliance posture.
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What is the typical shape of this engagement?
AWS engagements at Devlyn typically run as one senior DevOps or platform engineer plus shared backend for $5,500–$10,000/month, covering infrastructure architecture, CI/CD pipeline design, and cost-optimisation strategy. This scales to a two- or three-engineer pod when the roadmap splits into parallel lanes across platform infrastructure (networking, compute, storage), data-pipeline and analytics (Kinesis, Glue, Athena), and security and compliance (GuardDuty, Config, CloudTrail, SCPs). Pods share a single retainer with flexible allocation. undefined
Scope the work
If your Real Estate roadmap is shaped, book a 30-minute discovery call. We will validate if a AWS pod is the right fit, and if not, what shape is.