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# Software Engineer

- **Company:** Marvin
- **Location:** Los Angeles, CA, United States (Remote available)
- **Experience:** Expert
- **Salary:** $160,000.0 - $190,000.0
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), JavaScript (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Big Data, Software as a Service, Code Generation, Code Review, Databases, Continuous Integration, Relational Databases, Cursor, Programming Tools, Distributed Systems, Infrastructure as a Service (IaaS), Information Extraction, PostgreSQL, Node.Js, Open Source Technology, Software Architecture, Next.js, Software Systems, TypeScript, Management of Software Versions, Web Applications, Cloud Platform System, ReactJS, Retrieval-Augmented Generation, Large Language Models, Claude Code, Grafana, Prompt Engineering, Cypress (Programming Language), Caching, Backend, Langfuse — LLM Observability and Analytics Platform, Agentic-AI, Kotlin, AI Platforms, Stripe, LangSmith, Information Technology, Low Latency, Influxdb, Playwright, Sentry, JestJS, Terraform, Docker
- **Published:** October 28, 2026
- **Apply:** https://www.builtincolorado.com/job/senior-software-engineer/11926338?handler=ApplyRedirect

## About the Role

* 5+ years building production web applications, with deep TypeScript, React, and Node experience. Next.js is a strong plus.
 * Comfort across the stack: relational data modeling (we use Prisma and Postgres), auth flows, caching, background jobs, and cloud deployment (AWS, Docker, Terraform or similar).
 * A real testing habit at every layer: unit, component, and end-to-end. We use Vitest, Storybook, Cypress, and Playwright.
 * Strong product judgment and the ability to work directly with design, clinical, and partner-facing teammates.

## Description

We're hiring a senior full-stack engineer who has made AI a core part of how they build software, not a novelty. This is not a machine learning research role. You won't train models or tune GPUs. You will ship product in a modern TypeScript/Next.js stack, and you'll do it with AI woven into both the product and your own workflow.

Two things distinguish this role from a standard senior web position:

 1. You build with AI. You've moved well past autocomplete. You direct agentic coding tools to do real, multi-step work, you know exactly where they break, and you own every line they produce.
 2. You build AI into the product. You've shipped LLM-backed features to real users and lived with them in production: prompts, tool calls, evals, tracing, cost, latency, and failure modes.

What you'll do

 * Own features end to end across our Next.js/React/TypeScript app, Prisma/Postgres backend, and AWS infrastructure.
 * Extend our AI coach and build new LLM-powered member experiences: retrieval over benefits data, structured extraction, guided flows, and agentic tool use against our own APIs.
 * Design evaluation and observability for AI features so we know when they get worse, not just when they crash.
 * Push our AI-assisted development practice forward: agent instructions, reusable skills, hooks, MCP integrations, and review practices that keep quality high as velocity climbs.
 * Handle sensitive health data responsibly. PHI boundaries, redaction, audit trails, and vendor data agreements are part of the design, not an afterthought.
 * Review code, whether written by a human or an agent, with a critical eye. Mentor teammates and raise the bar on testing and reliability., * Daily, expert use of agentic coding tools such as Claude Code, Cursor, or Codex. You write project instructions and reusable skills for your agents, hand them multi-step tasks, and review the output like a senior reviewer, not a rubber stamp.
 * Hands-on experience shipping LLM features: prompt design and versioning, structured outputs, tool/function calling, streaming UIs, retrieval-augmented generation, and multi-turn conversation state.
 * You've run evals and traced production LLM traffic (LangSmith, Braintrust, Langfuse, or homegrown), and you can explain what changed the last time a model version bumped underneath you.
 * You understand the cost, latency, and quality triangle and have made real trade-offs: model selection, caching, prompt compression, and fallback strategies.
 * Clear-eyed about limits. You know when an LLM is the wrong tool, how to constrain one when it's the right tool, and how to keep a hallucination from ever reaching a member.

Nice to have

 * Healthcare, benefits, or other regulated-data experience (HIPAA, SOC 2).
 * Building MCP servers or internal agent tooling for a team.
 * Experience with Clerk, Stripe, or Sentry.
 * Contributions to AI developer tooling, open source or internal.

How we work

AI is part of our engineering culture, not a side experiment. Our repository ships with agent configuration, we maintain shared skills for code review and security checks, and we expect engineers to spend more of their time on judgment and less on typing. We also expect the opposite discipline: no unreviewed AI-generated code lands, and "the agent wrote it" is never an explanation for a bug.
Compensation and benefits, Develop and maintain scalable Java and Kotlin backend services for NinjaOne's SaaS backup and recovery platform. Design high-availability features supporting backup, archive, restore, and download workflows at large scale. Collaborate with globally distributed engineering teams, own architecture and design decisions, mentor engineers, optimize databases and distributed systems, and deliver reliable production software using technologies including AWS, PostgreSQL, Redis, Kafka, and REST frameworks., Drives performance engineering and scalability across software systems by identifying bottlenecks, optimizing code, queries, databases, and architecture, and implementing fixes. Builds performance frameworks, data-generation tools, benchmarks, and CI/CD automation using k6, JavaScript, Grafana, and InfluxDB. Establishes performance standards, investigates distributed systems and cloud environments, documents architectural decisions, and collaborates with engineering teams to improve throughput, latency, reliability, and efficiency.
Top Skills: AWSAzureBashC++Ci/CdGCPGoGrafanaInfluxdbJavaJavaScriptK6KotlinPostgresPython
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