Senior Software Engineer, Platform (Developer Experience)
关于 ECP ECP 是一个领先的 SaaS 解决方案，使老年社区能够更好地照顾其居民.ECP 在8,000多个社区中使用。我们希望通过增加用户数量和扩大我们的服务范围来进一步扩展客户开发和发布新产品。老年生活是软件深度不透的，ECP 是行业最大且增长最快的软件公司之一。我们最近筹集了一轮增长资本，以重投资我们的产品，技术和上市。我们的使命是建立世界级软件，以提高老年人的生活质量，改善我们的客户的临床，业务，合规和运营性能。角色基础工程是 ECP 平台组织中的新功能。它的宪章是从代码到生产的道路：工程师开发的环境，建造和运输他们的工作的管道，运行的基础设施以及使所有事情快速的工具。你将成为第一个被聘请的工程师，向开发者经验管理人员报告。每个交付团队都在你构建的东西上完成。现在，生产基础设施在 AWS 上是云形式，CI 分布在不止一个系统中，工程师们都在共享的长期环境中工作。我们接下来去开发者环境和基础设施作为代码是真正开放的，你会有助于决定它。你将从内部循环开始，一天中的一部分工程师花费在他们编程之前到达管道，然后向外进入管道和底层的 AWS 基础设施。的工作是手动的。你会写基础设施代码和构建工具，你会坐在我们的生产足迹运行的云工程师旁边，并随他们一起进行生产工作。堆。新代码是 Node 和 TypeScript.我们正在从 ColdFusion 的传统平台上迁移，这两者将共存一段时间，所以你构建的东西必须为两个服务。你不会写 ColdFusions.SQL Server 和 PostgreSQL,单元化和服务的混合物，采用域名驱动设计和事件驱动架构，都在 AWS 上。这是一个多租户 HIPAA 产品。工程师需要现实环境和完全可见性进入自己的系统，没有内部居民数据，这种限制塑造了大部分活动。
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About ECP
ECP is a market-leading SaaS solution that enables senior living communities to better care for their residents. ECP is used in over 8,000 communities. We're looking to further expand by increasing the number of customers that use our software and increasing the scope of how we serve our customers by developing and releasing new products.
Senior living is deeply under-penetrated with software and ECP is one of the largest and fastest-growing software companies in the industry. We recently raised a growth round of equity to reinvest in our product, technology, and go-to-market. Our mission is to build world-class software that improves the quality of life for seniors and improves clinical, business, compliance, and operational performance for our customers.
The Role
Foundation Engineering is a new capability in ECP's Platform organization. Its charter is the path from code to production: the environment an engineer develops in, the pipeline that builds and ships their work, the infrastructure it runs on, and the tooling that makes all of it fast. You'd be the first engineer hired into the developer experience side of it, reporting to the Engineering Manager for Developer Experience. Every delivery team ships on top of what you build.
Most of it is still ahead of us. Production infrastructure is CloudFormation on AWS today, CI is spread across more than one system, and engineers work in shared, long-lived environments. Where we go next on developer environments and infrastructure-as-code is genuinely open, and you'd have a hand in deciding it.
You'd start on the inner loop, the part of the day an engineer spends before their code ever reaches the pipeline, then move outward into the pipeline and the AWS infrastructure underneath it. The job is hands-on. You'll write infrastructure code and build tooling, and you'll sit next to the cloud engineers who run our production footprint and pick up production work alongside them.
The stack. New code is Node and TypeScript. We're migrating off a ColdFusion legacy platform, and the two will coexist for a while, so what you build has to serve both. You won't write ColdFusion. SQL Server and PostgreSQL, a mix of monolith and services, adopting domain-driven design and an event-driven architecture, all on AWS. This is a multi-tenant HIPAA product. Engineers need realistic environments and full visibility into their own systems without the resident data inside them, and that constraint shapes most of what you'll design. Our AI coding tools run on Bedrock inside our own AWS account for the same reason.
What You'll Build
The inner loop. Replace shared, slow-to-provision environments with ephemeral ones an engineer can stand up on demand, and solve the multi-tenant test data seeding that makes them realistic enough to trust. Cut local build and test times. Establish golden paths: opinionated, documented ways to build, test, and run a service, so the answer to "how do I start" is one page and one command.
The path to production. Get us building an artifact once and promoting it across environments instead of rebuilding for each one, and give engineers a feature flag system they trust enough to pull deploy and release apart. Those two are what the rest of our continuous delivery plans are waiting on. Make dependency scanning, secrets detection, and static analysis default steps on every build, and move teams onto a common pipeline as we consolidate. We're a small team and we'd rather adopt a good tool than write one, so knowing when to buy is part of the job.
The infrastructure underneath it. You'll write the AWS and infrastructure-as-code that your tooling and our environments run on, working alongside the cloud engineers who own our production footprint, and carry the pager for what you build.
Tooling for AI-assisted development. Our engineers build with AI today, and generating code has gotten far cheaper than verifying it. You'd own pieces of what closes that gap: deterministic builds, test feedback fast enough to stay inside the loop, sandboxed execution, review gates for agent-authored changes, and platform capabilities exposed to agents through MCP.
What Success Looks Like
At six months, a build runs once and that same artifact moves through every environment, and engineers have feature flags they rely on to deploy without releasing. At least one delivery team works against ephemeral environments with realistic seeded data.
Consolidated CI, observability that lets an engineer see their own system in production, and an internal developer portal follow from that foundation.
Requirements
What We're Looking For
Required
· You've built and run production AWS infrastructure and expressed it as code, with Terraform, CDK, Pulumi, or CloudFormation. Networking, IAM, and container workloads are things you've configured yourself, and you've carried a pager for infrastructure other engineers depended on.
· You've built or substantially rebuilt a CI/CD system that other engineers ship through, and you can say what got faster and how you measured it. Running a pipeline someone else designed isn't the same job.
· You've made a real system runnable outside production, whether that's ephemeral environments, test data for a multi-tenant application, or containerized local development that engineers besides you actually ran.
· Name a tool or service you wrote that other engineers used every day, and what it did for them. Much of this job is software.
· You've built something for engineers outside your own team, and you can talk about both a time it worked and a time nobody adopted it.
· You've moved other engineers along in how they use AI. It's already how you work yourself, and you know where it holds up and where it needs a human check. We expect our engineers to advocate for this.
Preferred
· Feature flag platforms and progressive delivery
· Kubernetes or ECS at production scale
· Observability built on OpenTelemetry, distributed tracing, or structured logging, especially where the data itself is sensitive
· HIPAA-regulated or other compliance-sensitive environments
· Bitbucket Pipelines, Jenkins, Azure DevOps, or GitHub Actions
· Test automation frameworks, or contract testing in an event-driven system
· Building alongside a legacy platform mid-migration, without the luxury of waiting for it to finish
· Node and TypeScript, internal developer portals, MCP servers
Originally posted on Himalayas