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Senior Full Stack Software Engineer
Life Line ScreeningUnited States - Remote, United StatesRemotefull_timeVerifiedPosted 19 Aug 2026
About the role
Senior Full Stack Software Engineer
TypeScript · React · Node.js · GraphQL · Event-Driven Architecture · AWS Serverless · AI-Assisted Engineering
We use a modern stack and SDLC, this is an AI-native engineering role. Our software development lifecycle is built around agentic AI: coding agents plan, implement, test, and review alongside us across the full pipeline. We expect senior engineers to be fluent operators of these tools — directing agents with precise intent, engineering the context they work from, and rigorously verifying what they produce. The bar for correctness, security, and maintainability does not move because an agent wrote the code; if anything, it rises. You will spend less time typing boilerplate code and more time specifying, orchestrating, reviewing, and owning outcomes.
TypeScript · React · Node.js · GraphQL · Event-Driven Architecture · AWS Serverless · AI-Assisted Engineering
Overview
We’re looking for a Senior Full Stack Software Engineer to build and evolve modern, cloud-native applications. You’ll own features end-to-end — from designing performant React/TypeScript user experiences to building event-sourced Node.js services and GraphQL APIs running serverless on AWS. You’ll partner closely with product and design, contribute to system architecture in an event-driven, service-oriented environment, and help strengthen engineering practices around CI/CD, automated testing, observability, and security-by-design.We use a modern stack and SDLC, this is an AI-native engineering role. Our software development lifecycle is built around agentic AI: coding agents plan, implement, test, and review alongside us across the full pipeline. We expect senior engineers to be fluent operators of these tools — directing agents with precise intent, engineering the context they work from, and rigorously verifying what they produce. The bar for correctness, security, and maintainability does not move because an agent wrote the code; if anything, it rises. You will spend less time typing boilerplate code and more time specifying, orchestrating, reviewing, and owning outcomes.
Key Responsibilities
Product & Platform Delivery- Own and deliver end-to-end product features from discovery and design through production support.
- Build high-quality, accessible (WCAG 2.2 AA), and performant user interfaces using React and TypeScript.
- Design and implement backend services and APIs using Node.js and GraphQL, with clear contracts and versioning strategies.
- Develop and operate cloud-native and serverless workloads on AWS, including Lambda, EventBridge, Aurora, SQS/SNS, and DynamoDB.
- Contribute to service-oriented, event-driven, and event-sourced architectures that scale reliably and evolve safely over time.
- Commit clean, maintainable, well-documented code and participate in thoughtful code reviews that raise the standard for the whole team.
- Contribute to architecture decisions and lightweight design records (ADRs, RFCs) that keep intent and trade-offs discoverable — by humans and by agents.
- Work agent-first by default. Use coding agents (e.g., Claude Code, GitHub Copilot) as the primary implementation surface for well-scoped work, escalating to hands-on coding.
- Practice spec-driven development. Translate product intent into precise, codebase-grounded specifications, acceptance criteria, and task decompositions that an agent can execute.
- Engineer the context, not just the prompt. Author and maintain the artifacts agents depend on: repository instruction files, coding standards, architectural conventions, domain glossaries, reusable prompt and skill libraries, and golden reference implementations.
- Orchestrate multi-agent workflows. Decompose larger initiatives into parallelizable agent tasks, run and supervise concurrent agent sessions, and integrate their output into coherent, reviewable changes.
- Extend the agent toolchain. Collaborate with teammates to build and maintain MCP servers, tools, and integrations that give agents safe, scoped access to our repositories, ticketing, documentation, observability, and internal services.
- Build AI-enabled product features where they create real user value — integrating LLM APIs, retrieval pipelines, and agentic workflows with attention to latency, cost, failure modes, and graceful degradation.
- Evaluate what you ship. For AI-powered features, define and maintain evals, regression suites, and quality benchmarks; monitor for hallucination, prompt injection, and drift.
- Collaborative & Team-Centric.
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