AWS Development
2muchcoffee is an AWS development company. Every engineer on our team ships and runs production workloads on EC2 and S3, with Lambda for serverless work, and a dedicated specialist for GPU and AI infrastructure when a product needs self-hosted inference at real scale. Building software since 2015, rated 5.0 on Clutch across 26 reviews. Senior engineers, dedicated to your product or embedded in your team.
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Why teams pick us for AWS
Senior engineers, not juniors
The people who scope your build are the people who ship it. More than eleven years shipping software, and a 5.0 rating on Clutch across 26 reviews.
The whole team, not one calendar
EC2 and S3 are baseline skills across every engineer we have. A standard AWS build does not wait on a single specialist's availability.
A real specialist for the hard part
GPU servers and self-hosted AI infrastructure run through one engineer who does this daily, not whoever happens to be free that week.
Capabilities
What we build on AWS
AWS is the baseline every engineer on our team ships on, not a specialty a couple of people happen to have picked up.
Application infrastructure
EC2 for compute, S3 for storage, RDS or Aurora for the database, CloudFront in front of it. The standard production stack behind most of the apps we ship, sized to what the product actually needs.
Serverless and event-driven backends
Lambda functions behind API Gateway for workloads that scale to zero between requests, and event-driven pipelines with SQS and EventBridge instead of a server that sits idle most of the day.
Containers on ECS and Fargate
Dockerized services on ECS or Fargate when a workload needs more than a single Lambda invocation, without taking on a Kubernetes cluster you do not need yet.
GPU and self-hosted AI infrastructure
EC2 GPU instances for self-hosted inference, speech-to-text, and model workloads that should not run through a third-party API, architected by the person on our team who does this daily.
Migration and cost architecture
Moving an app onto AWS from another host or from a single server, and the follow-up work most teams skip: right-sizing instances, reserved capacity, and catching the idle resources that quietly inflate the bill.
The stack
The AWS stack we work in
From compute and storage through to the identity and monitoring layer around them.
How we build
How we scope AWS work
An AWS build fails most often on sizing, not on the services themselves: an over-provisioned setup that costs more than the product earns, or an under-provisioned one that falls over at the first real traffic spike. We scope for the load you actually have, not the load a template assumes.
Compute, storage, and traffic patterns, before any service gets picked. A background job and a user-facing API are not sized the same way.
Serverless where the traffic is spiky or low-volume, containers or dedicated instances where it is steady, so you are not paying for capacity you do not use.
GPU instances are expensive by the hour. We reach for them only when a self-hosted model genuinely needs one, and size the instance class to the actual workload.
CloudWatch and cost alarms configured before launch, so a runaway process or a cost spike surfaces immediately instead of at the end of the month.
Specialty
AI and GPU infrastructure on AWS
Self-hosted inference and speech-to-text are a different discipline from standard app hosting, and it shows up in the AWS bill fastest of anywhere in the stack.
Self-hosted over API calls, when it matters
Some products cannot send audio or user data to a third-party inference API. We run the model ourselves on GPU instances, so data never leaves infrastructure you control.
Speech-to-text at production scale
Architecture for transcription pipelines that hold up past a demo: queuing, GPU instance sizing, and the batching that keeps a speech-to-text workload from becoming the most expensive line in the bill.
One person who does this daily, not occasionally
Oleg Logvin runs our GPU and AI-infrastructure work day to day. The rest of the team ships standard AWS builds; the self-hosted inference and GPU-architecture decisions run through the person who owns that specialty.
Read more on the architecture
We have published a full guide to speech-to-text technology and the infrastructure it takes to run it at scale, covering the same territory this work lives in. Read the guide
Engagement models
Work with us how you need
Pick the model that fits your stage. You can change it as your roadmap changes.
Dedicated developer
One senior engineer, full-time on your AWS infrastructure and managed by you. Best for an ongoing roadmap.
Dedicated team
A cross-functional pod of engineers, design, and QA, ready to ship an AWS-backed product end to end without growing headcount.
Project-based
A scoped build, migration, or cost-architecture review, delivered end to end against a fixed plan, price, and timeline.
Compare
Why a dedicated AWS team beats the alternatives
How hiring a senior AWS engineer through us compares to building in-house or going freelance.
Have an AWS build or migration in mind?
Proof
Read the work before you hire
Our open-source Angular library, used by thousands of startups. Public code, not a claim on a page.
A full production write-up of a self-hosted retrieval system: hybrid search, grounding, and the eval loop that keeps it honest. The same self-hosted-infrastructure discipline this page is about, applied to a real production system.
Questions
AWS development, answered
Do all your engineers know AWS, or is it one specialist?
EC2 and S3 are baseline skills across the whole team, so a standard AWS build does not wait on one person. GPU and self-hosted AI infrastructure is a real specialty on top of that baseline, run by one engineer who does it daily rather than occasionally.
Can you migrate our app onto AWS from another host?
Yes. We size the target architecture to your actual traffic and data first, then migrate with a plan rather than a lift-and-shift that just moves the same over-provisioning to a new bill.
What if our AWS bill is already too high?
That is usually a sizing problem, not a services problem: over-provisioned instances, no reserved capacity, or idle resources nobody turned off. We review the actual usage before recommending anything.
Do you build serverless or containerized architectures?
Both, chosen by the workload. Lambda and API Gateway for spiky or low-volume traffic, ECS or Fargate for steady workloads that need more than a single function invocation.
How do you engage, and how fast can you start?
Three ways: one dedicated senior engineer, a cross-functional pod, or a scoped fixed-plan project. We scope the work on a short call and start once the plan is agreed, so you are not waiting weeks to begin.
How much does AWS development cost?
It depends on scope and engagement model, so we do not quote a flat number up front. A dedicated engineer is a monthly rate, a scoped project is a fixed price against a plan. Tell us what you are building and we come back with an estimate before any work starts.
Who owns the AWS account and the code?
You do, from day one. The AWS account, the infrastructure-as-code, and the application code are all yours, whether we embed in your team or deliver a fixed-scope project.
Building or moving to AWS?
Tell us what you're running and we'll tell you honestly how we would size and ship it.
Talk to our team→Tell us about your AWS project
Our team contacts you within 24 business hours
We collect all the key requirements from you
The team of developers prepares estimation
We can sign NDA since we respect the confidentiality of our clients