Senior AI-Native Product Engineer - Senior | Zenara Health
位置:远程 - 印度类型:全职工作时间:所有会议和现场合作都在美国太平洋时间上午6点到12点之间发生。需要参加该窗口。你的剩余的工作是你安排的。承诺:每周约50小时行业:医疗技术经验是最好但不是强制性的公司关于 Zenara Health 是一个科技为导向的心理健康组织,专注于提高行为保健服务的访问量,质量和运营效率。我们为行为卫生诊所构建临床软件,包括评估和禅流等产品。我们是一家初创企业,而非部门。我们正在建立一个小型,高所有权的 AI 原生团队,使用现代代理工具来创建软件更快,更加谨慎和更强大的责任。关于角色我们正在寻找一名高级 AI 原生产品工程师,谁可以从要求到生产中进行有意义的产品工作。这不是仅仅是用人工智能自动完成的人的一个职位。也不是拒绝使用 AI 并想手动编码一切的人的一项职位。你将使用 AI 编码代理,如 Clode Code,Codex,Cursor 等类似系统来加速开发但你仍然负责运输的一切架构,代码质量,测试,安全和生产行为。今天,太多高级工程工作取决于我们的工程主管。这次聘请创造了第二个独立的技术所有者,可以快速与代理商一起运送而不降低质量..这里是测试:你能否采取产品要求,分解成可建造的部分,智能地委托给代理人,审查出口,调整错误,证明功能有效,并完成结局?我们不寻找一个无法编码的快速操作员。我们不是寻求与代理商合作拒绝的传统工程师。我们需要两者:强大的工程判断和人工智能原生杆。我们的人工智能-原生工程愿景 我们正在建设一种工程系统,其中少数高能力的工程师可以指导机组设计,实施,测试,审查,记录和改进软件。目标不是消除工程责任。目标是提高杆同时使质量更可衡量的。你将帮助塑造这在 Zenara 上如何工作,包括:· 打破产品要求成为代理执行任务
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Location: Remote - India
Type: Full-time
Working Hours: All meetings and live collaboration happen between approximately 6:00 PM and 12:00 AM IST, overlapping US Pacific Time. Attendance in that window is required. Your remaining work is yours to schedule.
Commitment: Approximately 50 hours per week
Industry: Healthcare technology experience is preferred but not mandatory
About the Company
Zenara Health is a technology-oriented mental healthcare organization focused on improving access, quality, and operational effectiveness in behavioral healthcare. We build clinical software for behavioral-health clinics, including products such as Assess and Zenflow.
We are a startup, not a department. We are building a small, high-ownership, AI-native team that uses modern agentic tools to create software faster, more carefully, and with stronger accountability.
About the Role
We are looking for a Senior AI-Native Product Engineer who can take meaningful product work from requirement to production.
This is not a role for someone who merely uses AI autocomplete. It is also not a role for someone who refuses to use AI and wants to code everything manually.
You will use AI coding agents such as Claude Code, Codex, Cursor, and similar systems to accelerate development — but you will remain accountable for the architecture, code quality, tests, security, and production behavior of everything you ship.
Today, too much senior hands-on engineering work depends on our Head of Engineering. This hire creates a second independent technical owner who can ship quickly with agents without lowering quality ..
Here is the test: can you take a product requirement, break it into buildable pieces, delegate intelligently to agents, review the output, debug what is wrong, prove that the feature works, and carry it over the finish line?
We are not looking for a prompt operator who cannot code.
We are not looking for a traditional engineer who refuses to work with agents.
We need both: strong engineering judgment and AI-native leverage.
Our AI-Native Engineering Vision
We are building toward an engineering system where a small number of highly capable engineers can direct fleets of agents to design, implement, test, review, document, and improve software.
The goal is not to remove engineering accountability. The goal is to increase leverage while making quality more measurable.
You will help shape how this works at Zenara, including:
- Breaking product requirements into agent-executable tasks
- Designing useful context for agents
- Reviewing and correcting agent-written code
- Creating tests that actually detect failure
- Preventing agent-created architectural drift
- Improving release confidence
- Mentoring junior engineers in AI-native workflows
- Setting standards for human review, quality gates, and production ownership
You will be one of the people defining how software gets built here.
What You’ll Do
- Design, build, test, deploy, and maintain full-stack product features across Zenara’s clinical products.
- Own features end to end, from an agreed requirement through task breakdown, implementation, testing, release, and production follow-up . .
- Use AI coding agents to accelerate implementation, refactoring, debugging, testing, and documentation.
- Review every agent-generated change with the skepticism of a senior engineer.
- Debug and fix code manually when AI output is wrong, incomplete, or misleading.
- Build and validate tests that prove the feature works — including tests that fail when the code is wrong.
- Own production issues in your area: diagnose, fix, document, and prevent recurrence . .
- Mentor and review work from junior engineers.
- Raise risks early, keep tickets current, and prevent delivery surprises.
- Help define Zenara’s standards for AI-native engineering, code review, testing, and production readiness.
What We’re Looking For
- Strong full-stack product engineering experience across APIs, databases, permissions, integrations, and user-facing workflows .
- Real experience using AI coding agents for multi-step engineering work, not just autocomplete .
- Strong ability to read, debug, and fix code without AI.
- Good judgment when reviewing AI-generated code and AI-generated tests.
- Experience owning production systems or production incidents.
- Comfort working across frontend, backend, data, integrations, and infrastructure-adjacent concerns.
- Clear written communication and strong ownership.
- Comfort with ambiguity, fast feedback cycles, and startup pace.
Our Current Stack
You do not need to know every tool before joining, but you should be able to learn quickly across a modern TypeScript product stack.
- TypeScript
- Node.js, Hono
- React
- Prisma, PostgreSQL
- Redis, BullMQ
- Playwright
- Azure AKS, Blob Storage, Azure Monitor / OpenTelemetry
- Terraform, Helm, CI pipelines
- Medplum / FHIR
- Flowable
- Claude Code, Codex
- Dify-based AI workflows
What “AI-Native” Means for This Role
For this role, being AI-native means you can:
- Translate product requirements into clear agent tasks.
- Know when to delegate to agents and when to take over manually.
- Review AI output deeply enough to catch hidden bugs.
- Validate behavior through tests, logs, and production evidence.
- Prevent agents from introducing unnecessary complexity.
- Maintain architectural consistency across agent-written changes.
- Use AI to move faster without outsourcing your judgment.
Nice to Have
- Healthcare, health-tech, or regulated-data experience.
- HIPAA or patient-data handling experience.
- Deep TypeScript, React, and Node.js experience at production scale.
- Experience mentoring junior engineers.
- Early-stage startup experience.
What Success Looks Like
In your first 30 days, you will ship one bounded feature through a verified release, leave clear maintenance notes, and help a junior developer complete one independently reviewed change ..
Within your first 90 days, you will own a product area, ship features regularly with agents, handle production issues in that area without depending on the Head of Engineering, and review junior engineering work.
Over time, success means becoming a trusted technical owner of a major product area and helping set the team’s agentic development practices while improving delivery speed and keeping escaped defects low.
Schedule
Live collaboration requires overlap with the US team. For engineering roles, the current collaboration window is approximately 6:00 PM to 12:00 AM IST, though final expectations should be confirmed during the hiring process.
Outside required meetings and live collaboration, we care about output, reliability, and ownership.
Compensation and Benefits
- Competitive compensation, based on demonstrated ability and experience
- Fully remote work
- Equipment allowance
- Direct and regular access to the founder and Head of Engineering
- Meaningful ownership in a fast-moving startup environment
Who Will Thrive in This Role
This role is well suited to someone who:
- Loves building product, not just writing code.
- Uses AI aggressively but does not trust it blindly.
- Takes ownership without waiting for detailed instructions.
- Can debug AI-generated code by hand.
- Cares about tests, evidence, and production behavior.
- Wants to help define how AI-native engineering works in practice.
You may struggle if you need detailed instructions for every task, can only code manually, can only prompt but not debug, or treat passing tests as proof without understanding what they actually verify.
If you want to help build clinical software and define how AI-native product engineering works in the real world, we would love to hear from you.
Originally posted on Himalayas