AI Native Software Engineer

Job Description v2.0

We are seeking an Software Engineer to build next-generation software products through AI-powered engineering practices, rapid product development, and modern software delivery methodologies.

This role goes beyond traditional software development. You will be responsible for leveraging AI as a force multiplier throughout the software development lifecycle-from requirements analysis and solution design to implementation, testing, deployment, and operations.

As an AI-Native Software Engineer, you will operate within AI Harness Engineering environments: AI-powered development ecosystems that integrate AI agents, copilots, automation workflows, and intelligent engineering practices to achieve 10x productivity, faster delivery, and higher software quality.

Responsibilities:

Software Development: Design, develop, test, and maintain scalable, secure, and high-quality software applications across frontend, backend, and cloud environments.

Rapid Product Development: Participate in rapid prototyping, MVP development, and iterative product delivery using AI-assisted workflows and customer feedback loops.

AI Harness Engineering: Utilize AI-powered development workflows including AI-assisted coding, testing, documentation, debugging, and engineering automation.

Technical Implementation: Translate business and technical requirements into working software solutions while adhering to engineering standards and best practices.

Solution Design and Implementation: Contribute to the design and implementation of scalable, secure, cloud-native, and AI-ready applications.

Collaboration: Work closely with Product, Design, Solutions, QA, and Engineering teams to deliver business value through technology.

Issue Resolution: Investigate, troubleshoot, and resolve technical issues while balancing short-term fixes with long-term maintainability.

Code Quality and Testing: Ensure software quality through code reviews, automated testing, and adherence to engineering standards.

Technical Debt Management: Identify and address technical debt while maintaining development velocity.

Continuous Improvement: Continuously improve development workflows, engineering practices, and personal productivity through AI and automation.

Documentation: Create and maintain technical documentation, knowledge articles, and implementation guides using AI-assisted workflows.

Learning and Innovation: Stay current with emerging technologies, AI development practices, and modern engineering trends.

Minimum Qualifications

Hands-on experience in software development with a strong understanding of the software development lifecycle.

Experience using AI-powered development tools to improve productivity and software quality.

Qualifications:

Minimum of 2 years of software engineering experience or equivalent demonstrated capability through projects and contributions.

Strong programming skills in one or more modern languages such as JavaScript/TypeScript, C#, Java, Python, Go, or similar technologies.

Experience building frontend, backend, API, or cloud-native applications.

Understanding of software architecture principles, design patterns, and engineering best practices.

Experience working with relational and/or NoSQL databases.

Familiarity with cloud platforms (AWS preferred), containerization (Docker), and modern deployment workflows.

Experience with CI/CD pipelines, version control systems (Git), and agile development methodologies.

Experience with AI-assisted software development, prompt engineering, AI copilots, agentic workflows, or AI platform integration is highly preferred.

Strong analytical, problem-solving, communication, and collaboration skills.

Ability to work effectively in a fast-paced environment focused on rapid product delivery and continuous innovation.

Detailed Expectation

AI-Native Software Development

Operate effectively within an AI-first software development environment.

Leverage AI tools to improve productivity while maintaining accountability for software quality and correctness.

Utilize AI for:

Requirements analysis

Technical design

Code implementation

Unit testing

Documentation

Debugging

Refactoring

Continuously improve AI utilization skills and engineering workflows.

Apply responsible AI practices to ensure secure, reliable, and maintainable software delivery.

Rapid Product Development

Contribute to rapid product development initiatives that move ideas from concept to production in days or weeks rather than months.

Support iterative delivery through rapid prototyping, MVP development, customer feedback loops, and continuous experimentation.

Leverage AI tools to accelerate:

Product discovery

Requirements generation

Technical design

Code implementation

Testing and QA

Documentation

Release preparation

Collaborate closely with Product Managers, Designers, Technical Leads, and Business Stakeholders to deliver business outcomes quickly and effectively.

AI Harness Engineering

Operate within AI Harnesses that orchestrate AI tools, agents, workflows, and human oversight throughout the software delivery lifecycle.

Utilize AI-powered engineering practices including:

AI-assisted coding

Multi-agent development workflows

Automated code review

AI-generated testing

AI-powered documentation

AI-assisted debugging

Contribute feedback and improvements to AI-enabled development processes.

Ensure AI-generated outputs are properly validated, tested, and aligned with engineering standards.

Technical Architecture & Solution Design

Contribute to the design and implementation of scalable, secure, resilient, and AI-ready systems.

Participate in architectural discussions and technical design reviews.

Apply modern engineering principles including:

Clean Architecture

Domain-Driven Design (DDD)

Event-Driven Architecture

CQRS

Microservices

API-First Design

Cloud-Native Architectures

Build solutions that can support future AI capabilities and intelligent automation requirements.

Engineering Excellence

Maintain high engineering standards across all software deliverables.

Implement and follow:

CI/CD pipelines

Automated testing

Infrastructure as Code

Security-by-Design

Observability and Monitoring

Write clean, maintainable, and well-documented code.

Balance development speed with software quality, maintainability, and long-term sustainability.

Continuously improve productivity through automation and AI-assisted workflows.

Team Development & Talent Growth

Participate actively in peer reviews, knowledge sharing, and collaborative engineering activities.

Continuously develop technical expertise and AI-native engineering skills.

Support onboarding and mentoring of junior engineers when appropriate.

Demonstrate ownership, accountability, and commitment to continuous improvement.

Contribute to a culture of innovation, experimentation, and engineering excellence.

Cross-Functional Collaboration

Partner closely with Product, Design, Solutions, Data, AI, QA, and Business teams.

Translate business requirements into effective technical solutions.

Participate in technical discussions, planning sessions, and solution reviews.

Communicate technical concepts clearly to both technical and non-technical stakeholders.

Contribute to successful product delivery through strong collaboration and teamwork.