Agentic Full-Stack Engineer

IndiaRemoteFull-timemid

EngineeringFullstack Developer

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Quick Summary

Overview

This role is for one of Weekday’s clientsSalary range: Rs 2000000 - Rs 5000000 (ie INR 20 - 50 LPA) Min Experience: 2+ yearsLocation: Remote (India),

Technical Tools

EngineeringFullstack Developer

Requirements

~2 min read

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 experience is preferred.
Practical familiarity with containerization, RESTful API design, and at least one of serverless or event-driven architecture.
Ability to independently own features from scoping and implementation through testing, review, and deployment.
Strong written communication skills and the 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 deviations from established architectural patterns.
Practical experience using GenAI tools such as Claude or ChatGPT for coding, research, drafting, summarization, data analysis, or workflow automation.
Understanding of GenAI limitations, including hallucination risks, context-window constraints, and data sensitivity boundaries.
Familiarity with prompt engineering, multi-step instructions, context setting, and iterative refinement of AI-generated outputs.
Comfort working with agentic AI workflows and willingness to learn how 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 team knowledge-sharing activities.

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 requiring current or future employer sponsorship.
Employment is contingent upon successfully completing a background check, including prior employment verification.

Responsibilities

~1 min read

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.
Critically review AI-generated code and specifications for correctness, security vulnerabilities, hallucinations, and alignment with existing architectural patterns.
Take ownership of assigned features throughout the development lifecycle, including testing, code reviews, deployment, and monitoring.
Contribute to API design and data modelling within an established microservices architecture.

Use and extend existing agentic workflows and engineering automation pipelines.
Build reusable automations for recurring engineering tasks and contribute to AI-powered development processes.
Follow human-in-the-loop review practices to ensure all AI-generated changes are evaluated before reaching production.
Explore opportunities to move beyond using GenAI tools towards designing 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 services responsible for real-time threat intelligence ingestion and delivery.
Apply secure-by-design principles throughout development.

Collaborate with security researchers to translate vulnerability intelligence into practical platform features.
Develop an understanding of exposure management, security tooling, vulnerability data, and threat intelligence.
Work with teams across the US and India, including attending 1–2 evening meetings per week to coordinate with India-based teams.
Integrate GenAI tools into everyday work while following data classification and responsible AI usage guidelines.

Exposure to security tooling, vulnerability data, or threat intelligence.
Experience working in codebases with established testing practices and continuous integration (CI) processes.
Familiarity with cloud-native security platforms and microservices architectures.