Company Description

Aurm is India’s first 24x7 automated bank locker facility, offering secure, technology-driven storage solutions for individuals and businesses. The company combines military-grade security with comprehensive insurance to provide peace of mind for customers’ most valuable assets. Aurm focuses on seamless, automated access and a premium customer experience, integrating advanced hardware and software systems.

The service is currently live in select communities and is expanding its footprint, creating opportunities to work on cutting-edge applied AI in a real-world, high-security environment.

Role Overview

Owns the technical design, development and delivery of software through secure, AI-native engineering practices. Drives technical execution, architecture decisions, engineering standards, code quality and the effective integration of AI agents into the software development lifecycle. This is a hands-on engineering role for an experienced software engineer who combines strong software engineering fundamentals with practical expertise in AI-assisted development, agentic engineering and automation.

The role is expected to lead by example through active participation in architecture, implementation, code reviews and problem-solving, while taking ownership of building and operating reliable, production-grade software.

Key Responsibilities

● Drive AI-native SDLC practices using coding agents and LLM tools across requirements, design, development, testing, code review, documentation and releases, with appropriate human oversight and quality gates.

● Drive technical architecture and design, ensuring scalability, security, performance,



reliability and maintainability while establishing engineering standards for code, APIs, data models, testing and deployment.

● Design and implement agentic workflows integrated with source control, project management, CI/CD, cloud and observability systems, incorporating context management, permissions, evaluation, guardrails and failure recovery.

● Own hands-on technical execution from requirements to production, solving complex problems, reviewing code and designs, troubleshooting production issues, reducing technical debt and improving engineering practices.

Ideal Candidate

● Has 5+ years of software engineering experience, with demonstrated technical ownership and experience delivering production-grade software.

● Has practical experience using AI coding agents and LLM tools across real-world software development workflows.

● Has experience building agentic engineering workflows integrated with development tools, infrastructure and operational systems, with an understanding of security and reliability considerations.

● Combines strong engineering fundamentals, architectural judgment and hands-on problem-solving with the ability to collaborate, guide peers and contribute to a small engineering team.

Required Experience





● Software Engineering Fundamentals: Strong experience in distributed systems, microservices, API design, data modeling, concurrency, caching, messaging and event-driven architectures.

● Technical Architecture and Engineering Quality: Experience designing scalable and secure systems, defining engineering standards and implementing automated testing, CI/CD, application security, observability and reliability practices.

● AI-Native SDLC: Hands-on experience using coding agents and LLM tools across requirements, architecture, development, code review, testing, debugging, documentation and releases, with appropriate human oversight and quality controls.

● Agentic Engineering and Automation: Experience building AI agent workflows integrated with engineering systems, understanding tool calling, context management, permissions, state, evaluation, guardrails and failure recovery, with demonstrated technical ownership.

Aurm Engineering Manifesto

- Build for outcomes, not activity.

Apply AI to amplify engineering judgment, automate the routine, and increase the value we deliver—not simply the amount of code we produce.
- Ship rapid, but engineer for production.

Favor small feedback loops, automation, observability, security, and reliability from the start.
- Own the system, not just the task.

Engineers are accountable for what they build, how it operates, and the outcomes it creates.
- Measure what matters.

Use data, baselines, and real-world outcomes to continuously improve our technology, products, and engineering organization

📌 Applied AI - Engineering Lead (Bengaluru)
🏢 Aurm
📍 Bengaluru