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Zenara Health

Behavioral health workflow software

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

AI Application Engineering +1Confirmed live in the last 24 hours
Full-timeRemote in IndiaNo salary listed

About the Job

Requirements

  • Approximately 5–8 years of professional software engineering experience, or equivalent demonstrated ability.
  • Experience owning delivery end to end, including planning and sequencing work and carrying a product through completion.
  • Strong full-stack development skills across modern frontend frameworks such as React, Next.js, or equivalent; backend technologies such as Python, TypeScript, or Node.js; REST, GraphQL, event-driven, or asynchronous system integrations; and relational and/or NoSQL databases.
  • Strong understanding of software architecture, API design, data modeling, testing, and production engineering.
  • Practical experience building with large language models or agentic artificial intelligence systems, beyond using artificial intelligence coding assistants.
  • Understanding of agentic artificial intelligence concepts including 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, evaluations, tracing and observability, guardrails and permission boundaries, and human-in-the-loop workflows.
  • Ability to critically assess artificial-intelligence-generated code and validate it through tests, reviews, security checks, and architectural reasoning.
  • Working knowledge of cloud infrastructure, containers, continuous integration and continuous delivery, 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, and common web application vulnerabilities.
  • Availability during required meeting overlap with US Pacific Time and commitment to approximately 50 hours per week.
  • Clear written and verbal communication skills.

Responsibilities

  • Design, build, test, deploy, and maintain full-stack product features.
  • Develop artificial-intelligence-native applications and workflows using autonomous agents, large language models, tools, APIs, retrieval systems, and structured data.
  • Build agentic systems that 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 while maintaining engineering quality.
  • Build and operate multi-agent workflows across product discovery, architecture, development, testing, security, deployment, and maintenance.
  • Define 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 to measure agent quality, accuracy, reliability, and business impact.
  • Develop safeguards against architectural drift, security vulnerabilities, unreliable code, and unnecessary complexity introduced by agents.
  • Implement protections against artificial-intelligence-specific risks, including hallucinations, prompt injection, excessive permissions, data leakage, and unreliable tool execution.
  • Measure software factory effectiveness using delivery speed, defect rates, test coverage, reliability, cost, and business outcomes.
  • Work with cloud infrastructure, continuous integration and continuous delivery 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.
  • Own work from initial problem definition through production deployment and ongoing improvement.
  • Continuously evaluate emerging agentic artificial intelligence frameworks, models, protocols, and development practices.
  • Gradually take ownership of coordinating the agent swarm and shaping the AI-native engineering organization.
  • Establish autonomous-agent workflows that improve engineering speed and quality, and improve the reliability, security, and observability of agentic systems.
  • Build repeatable workflows through which agents can implement, test, review, and document software.
  • Contribute to architectural decisions across application, artificial intelligence, data, security, and infrastructure layers.

Desired Qualifications

  • Experience in healthcare, health technology, clinical workflows, or regulated software environments.
  • Familiarity with healthcare data standards and requirements such as HIPAA, FHIR, HL7, protected health information handling, auditability, or role-based access control.
  • Experience with agent frameworks, orchestration systems, MCP, vector databases, or large-language-model observability and evaluation platforms.
  • Experience building multi-agent systems or long-running autonomous workflows.
  • Experience designing artificial-intelligence-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.

About the Company

Zenara Health

Behavioral health workflow software

Zenara Health is a healthcare technology company building workflow software for behavioral health practices. The company supports structured assessment, measurement, documentation, coordination, and care-program administration for clinical teams. It serves psychiatry, psychotherapy, primary-care, and health-system practices. Its operating model centers on clinician-designed software and operational workflows that prepare information while leaving diagnosis and treatment decisions to professionals. Teams work across product, engineering, clinical design, implementation, customer support, operations, and growth.

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Total funding
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