AI-Native Full-Stack Software Engineer / Technical Project Manager

We are looking for an AI-native Full-Stack Software Engineer who understands that AI-assisted software development goes far beyond using Cursor, Claude Code, or other coding assistants.

You will use and build autonomous agentic development workflows — delegating complex tasks to agents, designing effective context and tool architectures, evaluating outputs, and creating reliable systems in which AI agents can plan, execute, test, and iterate.

You should also be a strong software engineer capable of making sound architectural decisions and delivering production-grade applications across the stack. You will work across product development, AI systems, cloud infrastructure, security, testing, and deployment.

Here is the test. Are you someone who knows how to run a piece of work and get a product over the finish line? Could you build it yourself if you had to — but you get there faster with a team around you? We are not looking for a project manager who cannot code, and we are not looking for a coder who cannot run a project. We need both, in one person.

The difference in this role is who the team is. You will not be coordinating twenty engineers. You will be coordinating agents, and holding yourself to the same standard of delivery you would if they were people.

This is a hands-on role in a fast-moving startup. You will have meaningful ownership, work through ambiguity, learn quickly, and help shape both our product architecture and engineering culture.

We are building toward an AI-native software factory : an engineering system where coordinated swarms of specialized agents can translate product requirements into architecture, implementation, tests, security checks, documentation, deployments, and continuous improvements — with engineers providing direction, judgment, and governance.

You will help design and operate this software factory, including:

Agent roles and responsibilities

Multi-agent orchestration and delegation

Context and memory architecture

Tool access and permission controls

Testing and quality gates

Security and compliance checks

Evaluations, tracing, and observability

Human review and approval workflows

Feedback loops for continuous improvement

The goal is not to eliminate engineering accountability. It is to enable a small, highly capable engineering team to deliver software with dramatically greater speed, quality, and consistency.

As you grow in this role, you will have the opportunity to lead this software factory and direct a swarm of autonomous development agents . You will increasingly operate as the technical leader of an intelligent delivery system — while remaining hands-on with architecture, engineering standards, and critical technical decisions.

Design, build, test, deploy, and maintain full-stack product features.

Develop AI-native applications and workflows using autonomous agents, LLMs, tools, APIs, retrieval systems, and structured data.

Build agentic systems that can plan and execute multi-step tasks with appropriate observability, evaluation, permissions, and human oversight.

Use autonomous development agents to accelerate implementation, testing, debugging, refactoring, documentation, and code review without compromising engineering quality.

Build and operate multi-agent workflows across product discovery, architecture, development, testing, security, deployment, and maintenance.

Define clear agent responsibilities, communication patterns, permissions, escalation paths, and quality gates.

Design robust backend services, APIs, data models, integrations, and modern frontend experiences.

Contribute to system architecture and make practical decisions involving scalability, reliability, security, cost, and maintainability.

Create evaluation frameworks and feedback loops for measuring agent quality, accuracy, reliability, and business impact.

Develop safeguards that prevent agents from introducing architectural drift, security vulnerabilities, unreliable code, or unnecessary complexity.

Implement protections against AI-specific risks, including hallucinations, prompt injection, excessive permissions, data leakage, and unreliable tool execution.

Measure the software factory's effectiveness using delivery speed, defect rates, test coverage, reliability, cost, and business outcomes.

Work with cloud infrastructure, CI/CD pipelines, containers, logs, monitoring, secrets, environments, and production deployments.

Apply foundational cybersecurity practices across application development and infrastructure.

Collaborate directly with founders, product stakeholders, customers, and other engineers.

Take ownership from initial problem definition through production deployment and ongoing improvement.

Continuously evaluate emerging agentic AI frameworks, models, protocols, and development practices.

Gradually take ownership of coordinating the agent swarm and shaping the next generation of our AI-native engineering organization.

Approximately 5–8 years of professional software engineering experience , or equivalent demonstrated ability.

Experience owning delivery end to end, not only your own tasks. You have seen how a whole product goes together, you can plan and sequence the work, and you have carried something over the finish line. This matters as much as your coding ability — it is the half of the job that most engineers have never done.

Strong full-stack development skills across:

Modern frontend frameworks such as React, Next.js, or equivalent

Backend development using Python, TypeScript, Node.js, or similar technologies

REST, GraphQL, event-driven, or asynchronous system integrations

Relational and/or NoSQL databases

Strong understanding of software architecture, API design, data modeling, testing, and production engineering.

Practical experience building with LLMs or agentic AI systems — not only using AI coding assistants.

Understanding of agentic AI concepts such as:

Tool use and function calling

Planning and multi-step execution

Agent orchestration and delegation

Multi-agent collaboration

Memory and context management

Retrieval-augmented generation

Structured outputs and validation

Model selection and routing

Guardrails and permission boundaries

Human-in-the-loop workflows

Ability to assess AI-generated code critically and validate it through tests, reviews, security checks, and architectural reasoning.

Working knowledge of cloud infrastructure, containers, CI/CD, production monitoring, and deployment practices.

Basic understanding of cybersecurity principles, including:

Authentication and authorization

Encryption and secrets management

Secure API design

Dependency and supply-chain security

Data privacy and access controls

Common web application vulnerabilities

High ownership, curiosity, and comfort working in an ambiguous startup environment.

A strong desire to remain at the cutting edge of agentic AI and AI-native software development.

Clear written and verbal communication skills.

Availability for the required meeting overlap with US Pacific Time, and a commitment of approximately 50 hours per week.

For this role, being AI-native means you can:

Decompose complex engineering objectives into tasks that autonomous agents can plan and execute.

Design the context, tools, permissions, feedback loops, and verification mechanisms agents need to work reliably.

Coordinate multiple specialized agents while maintaining architectural and product consistency.

Determine when an agent can act autonomously and when human review is required.

Evaluate agent performance systematically rather than relying on impressive demonstrations.

Build reliable agent-powered product capabilities that work under real-world conditions.

Use AI to increase engineering leverage while remaining accountable for quality, security, and outcomes.

Treat agents as components of an engineering system — not simply as chat interfaces or code-generation tools.

Experience with any specific model or framework is useful, but we value your ability to understand and apply the underlying principles more than expertise in one particular tool.

Experience in healthcare, health technology, clinical workflows, or regulated software environments.

Familiarity with healthcare data standards and requirements such as HIPAA, FHIR, HL7, PHI handling, auditability, or role-based access control.

Experience with agent frameworks, orchestration systems, MCP, vector databases, or LLM observability and evaluation platforms.

Experience building multi-agent systems or long-running autonomous workflows.

Experience designing AI-based development workflows or internal engineering automation.

Familiarity with infrastructure as code, Kubernetes, serverless systems, or major cloud platforms.

Experience with security reviews, threat modeling, compliance, or privacy-sensitive applications.

Previous experience working in an early-stage startup.

Within your first several months, you will:

Ship meaningful full-stack features into production.

Establish effective autonomous-agent workflows that improve engineering speed and quality.

Contribute to architectural decisions across application, AI, data, security, and infrastructure layers.

Improve the reliability, security, and observability of our agentic systems.

Build repeatable workflows through which agents can implement, test, review, and document software.

Demonstrate strong ownership of projects from initial idea to measurable production outcomes.

Help the team remain at the cutting edge without adopting technology purely for novelty.

Begin taking meaningful ownership of the architecture and operation of our AI-native software factory.

Over time, success in this role means becoming capable of leading a software delivery function powered by a coordinated swarm of autonomous agents — setting direction, enforcing engineering standards, reviewing critical decisions, and continuously improving the system's speed and reliability.

Significant ownership and direct influence over product and technical direction.

Hands-on exposure to cutting-edge autonomous and agentic AI development.

The opportunity to help build an AI-native software factory from the ground up.

A path toward leading a coordinated swarm of specialized software-development agents.

Fast learning, rapid experimentation, and short feedback cycles.

A rigorous, high-accountability startup environment.

Challenging work alongside ambitious and curious teammates.

The opportunity to grow with the company and participate in the rewards of startup success.

A demanding but energetic, collaborative, and fun working culture.

This role is well suited to someone who:

Enjoys startup intensity and moving quickly through ambiguity.

Is deeply curious and learns aggressively.

Takes ownership rather than waiting for detailed instructions.

Understands that AI-generated output must still be validated and governed.

Wants to build the systems through which software will be created — not merely complete individual tickets.

Is excited by the prospect of eventually leading a software factory powered by autonomous agents.

Wants to help define how AI-native software engineering will work in practice.

If you want to do more than use AI as a faster code editor — and instead help build and lead an autonomous, agent-powered software factory — we would love to hear from you.