Full-Stack Engineer

Weekday (YC W21)

. Design, develop, test, and deploy full-stack features for a cloud-native cybersecurity SaaS platform .

Posted 11/11/2026full-timeUnited StatesJuniorMid-Level💰 ₹2,000,000 - ₹5,000,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in full-stack development for cloud-native cybersecurity SaaS platforms, with a strong focus on AI coding agents, secure coding practices, and microservices architecture. Capable of independently owning features from design through deployment while collaborating effectively across teams and time zones.

Highest-signal resume keywords

Full-Stack DevelopmentCloud-Native SaaS PlatformsAI Coding AgentsMicroservices ArchitectureAWS Cloud Platform

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Production-Grade Software DevelopmentRESTful API DesignContainerizationServerless ArchitectureAI Code ReviewData ModellingTesting PracticesContinuous IntegrationPrompt EngineeringSecurity Vulnerability Assessment

Soft Skills

Strong Written CommunicationCollaboration Across Time Zones

Tools & Technologies

GenAI ToolsClaudeChatGPTEngineering Automation PipelinesAgentic Workflows

Industry Keywords

CybersecurityThreat IntelligenceSecure-By-Design PrinciplesAI Security FundamentalsVulnerability Data

Tech Stack

Tools & technologies

AWSAzureCloudCyber SecurityGoogle Cloud PlatformMicroservices

About the role

Key responsibilities & impact

Design, develop, test, and deploy full-stack features for a cloud-native cybersecurity SaaS platform
Use AI coding agents to draft specifications, generate boilerplate, and accelerate implementation
Review AI-generated code and specifications for correctness, security vulnerabilities, hallucinations, and architectural alignment
Own assigned features through testing, code reviews, deployment, and monitoring
Contribute to API design and data modelling within an established microservices architecture
Use and extend agentic workflows and engineering automation pipelines
Build reusable automations for recurring engineering tasks and AI-powered development processes
Apply human-in-the-loop review practices before AI-generated changes reach production
Design and extend agent workflows and reusable AI capabilities
Build and maintain cloud-native SaaS services on AWS or other public cloud platforms
Work with containerized applications, RESTful APIs, and serverless or event-driven architectures
Support real-time threat intelligence ingestion and delivery services
Apply secure-by-design principles
Collaborate with security researchers to translate vulnerability intelligence into platform features
Work with teams across the US and India, including 1–2 evening meetings per week with India-based teams
Integrate GenAI tools into daily work following data classification and responsible AI guidelines

Requirements

What you’ll need

2+ years of experience building production-grade software, preferably within SaaS environments
Bachelor's degree in Computer Science, Information Technology, Engineering, or a related technical field, or equivalent practical experience
Working experience with at least one public cloud platform: AWS, GCP, or Azure; AWS preferred
Practical familiarity with containerization, RESTful API design, and serverless or event-driven architecture
Ability to independently own features from scoping and implementation through testing, review, and deployment
Strong written communication skills and ability to collaborate across time zones
Hands-on, daily experience using AI coding agents is mandatory
Ability to evaluate AI-generated code and specifications for hallucinations, security flaws, and architectural deviations
Practical experience using GenAI tools such as Claude or ChatGPT
Understanding of GenAI limitations, hallucination risks, context-window constraints, and data sensitivity boundaries
Familiarity with prompt engineering, multi-step instructions, context setting, and iterative refinement
Comfort working with agentic AI workflows and willingness to design and extend them
Awareness of AI security fundamentals, including prompt injection risks, data classification, sandboxed execution, and responsible handling of sensitive information
Willingness to adopt emerging AI tools and participate in AI adoption initiatives, hackathons, and knowledge-sharing activities
Exposure to security tooling, vulnerability data, or threat intelligence
Experience with established testing practices and continuous integration processes
Familiarity with cloud-native security platforms and microservices architectures
Candidates must reside in or within commuting distance of San Jose, California, or Albuquerque, New Mexico
Must be legally authorized to work in the United States without current or future employer sponsorship
Employment contingent upon successfully completing a background check, including prior employment verification