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Zenara Health is seeking a Senior AI-Native Product Engineer to take meaningful product work from requirements to production, leveraging AI coding agents while maintaining architecture, tests, security, and production behavior.
You will own features end-to-end, review AI-generated output, and mentor teammates. This role is fully remote with a 6:00 PM–12:00 AM IST collaboration window and a focus on AI-native engineering practices at Zenara.
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
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.
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.
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:
You will be one of the people defining how software gets built here.
You do not need to know every tool before joining, but you should be able to learn quickly across a modern TypeScript product stack.
For this role, being AI-native means you can:
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.
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.
This role is well suited to someone who:
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.